CN114638014A

CN114638014A - Image processing method, device and equipment based on privacy protection

Info

Publication number: CN114638014A
Application number: CN202210284438.1A
Authority: CN
Inventors: 曹佳炯; 丁菁汀
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2022-03-22
Filing date: 2022-03-22
Publication date: 2022-06-17

Abstract

The embodiment of the specification provides an image processing method, an image processing device and image processing equipment based on privacy protection, wherein the method comprises the following steps: determining a noise factor of a user image to be subjected to privacy protection processing based on the current environment; generating the counternoise of the user image based on the noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to carry out double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met.

Description

Image processing method, device and equipment based on privacy protection

Technical Field

The present disclosure relates to the field of image processing technologies, and in particular, to an image processing method, an image processing apparatus, and an image processing device based on privacy protection.

Background

In recent years, biometric identification technology has been widely used in many fields, such as the payment field, the access authentication field, the attendance field, and the like. Biometric identification generally involves several steps, such as acquisition, transmission, identification processing and storage of biometric images. In order to avoid the stored biometric image being stolen, thereby causing the privacy of the user to be revealed, the current storage process usually adopts some encryption algorithms to encrypt the biometric image and then store the biometric image. However, since the encryption algorithm is easily broken, there is still a risk that the privacy of the user is revealed.

Disclosure of Invention

One or more embodiments of the present specification provide an image processing method based on privacy protection. The method comprises the step of determining the noise factor of a user image to be subjected to privacy protection processing based on the current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And superposing the user image and the confrontation noise to obtain a target image. And generating an image file according to the preset credible access information of the user image and the target image and storing the image file. And performing double verification processing on whether the target image has illegal access or not based on the saved image file when the preset verification condition is determined to be met.

One or more embodiments of the present specification provide an image processing method based on privacy protection. The method comprises the step of determining the noise factor of a user image to be subjected to privacy protection processing based on the current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And carrying out superposition processing on the user image and the counternoise based on an intelligent contract in a block chain system to obtain a target image. And generating an image file according to preset credible access information of the user image and the target image based on the intelligent contract. And saving the image file to the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file is determined to meet the preset verification condition.

One or more embodiments of the present specification provide an image processing apparatus based on privacy protection. The device comprises a determining module, and the determining module is used for determining the noise factor of the user image to be subjected to privacy protection processing based on the current environment. The device also comprises a first generation module which generates the confrontation noise of the user image based on the noise factor through a generation model of the confrontation noise obtained by carrying out model training processing in advance. The device also comprises a superposition module which is used for carrying out superposition processing on the user image and the confrontation noise to obtain a target image. The device also comprises a second generation module which generates and stores an image file according to the preset credible access information of the user image and the target image. And performing double verification processing on whether the target image has illegal access or not based on the saved image file when the preset verification condition is determined to be met.

One or more embodiments of the present specification provide an image processing apparatus based on privacy protection. The device comprises a determining module, and the determining module is used for determining the noise factor of the user image to be subjected to privacy protection processing based on the current environment. The device also comprises a first generation module which generates the confrontation noise of the user image based on the noise factor through a generation model of the confrontation noise obtained by carrying out model training processing in advance. The device also comprises a superposition module which is used for carrying out superposition processing on the user image and the countermeasure noise based on an intelligent contract in the block chain system to obtain a target image. The device also comprises a second generation module which generates an image file according to the preset credible access information of the user image and the target image based on the intelligent contract. The device also comprises a storage module, which stores the image file into the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file meets the preset verification condition.

One or more embodiments of the present specification provide an image processing apparatus based on privacy protection. The apparatus includes a processor. The apparatus also comprises a memory arranged to store computer executable instructions. The computer-executable instructions, when executed, cause the processor to determine a noise factor for a user image to be privacy preserving based on a current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And superposing the user image and the confrontation noise to obtain a target image. And generating an image file according to the preset credible access information of the user image and the target image and storing the image file. And performing double verification processing on whether the target image has illegal access or not based on the saved image file when the preset verification condition is determined to be met.

One or more embodiments of the present specification provide an image processing apparatus based on privacy protection. The apparatus includes a processor. The apparatus also comprises a memory arranged to store computer executable instructions. The computer-executable instructions, when executed, cause the processor to determine a noise factor for a user image to be privacy preserving based on a current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And carrying out superposition processing on the user image and the counternoise based on an intelligent contract in a block chain system to obtain a target image. And generating an image file according to preset credible access information of the user image and the target image based on the intelligent contract. And saving the image file to the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file is determined to meet the preset verification condition.

One or more embodiments of the present specification provide a storage medium. The storage medium is used to store computer-executable instructions. The computer-executable instructions, when executed by the processor, determine a noise factor for a user image to be privacy-preserving based on a current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And superposing the user image and the confrontation noise to obtain a target image. And generating an image file according to the preset credible access information of the user image and the target image and storing the image file. And performing double verification processing on whether the target image has illegal access or not based on the saved image file when the preset verification condition is determined to be met.

One or more embodiments of the present specification provide a storage medium. The storage medium is used to store computer-executable instructions. The computer-executable instructions, when executed by the processor, determine a noise factor for a user image to be privacy-preserving based on a current environment. And generating the confrontation noise of the user image based on the noise factor by a generation model of the confrontation noise obtained by carrying out model training processing in advance. And carrying out superposition processing on the user image and the counternoise based on an intelligent contract in a block chain system to obtain a target image. And generating an image file according to preset credible access information of the user image and the target image based on the intelligent contract. And saving the image file to the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file is determined to meet the preset verification condition.

Drawings

In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and that other drawings can be obtained by those skilled in the art without inventive exercise.

Fig. 1 is a first flowchart of an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

fig. 2 is a second flowchart of an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

fig. 3 is a schematic flowchart of a privacy-based image processing method according to one or more embodiments of the present disclosure;

fig. 4 is a fourth flowchart illustrating an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

fig. 5 is a fifth flowchart illustrating an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

fig. 6 is a sixth flowchart illustrating an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

FIG. 7 is a schematic flow diagram illustrating a method for training a generative model of noise immunity provided in one or more embodiments of the present disclosure;

fig. 8 is a seventh flowchart illustrating an image processing method based on privacy protection according to one or more embodiments of the present disclosure;

fig. 9 is a schematic block diagram illustrating a first module of an image processing apparatus based on privacy protection according to one or more embodiments of the present disclosure;

fig. 10 is a schematic block diagram illustrating a second module of an image processing apparatus based on privacy protection according to one or more embodiments of the present disclosure;

fig. 11 is a schematic structural diagram of an image processing apparatus based on privacy protection according to one or more embodiments of the present specification.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in one or more embodiments of the present disclosure, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from one or more of the embodiments described herein without making any inventive step shall fall within the scope of protection of this document.

Fig. 1 is a flowchart illustrating an image processing method based on privacy protection according to one or more embodiments of the present disclosure, where the method in fig. 1 can be performed by an image processing apparatus based on privacy protection (hereinafter, simply referred to as an image processing apparatus), which may be deployed in a terminal device or a server; the terminal equipment can be a mobile phone, a tablet personal computer, a portable notebook, a desktop computer and the like; the server side can be an independent server or a server cluster consisting of a plurality of servers. As shown in fig. 1, the method comprises the steps of:

step S102, determining a noise factor of a user image to be subjected to privacy protection processing based on the current environment;

the user image to be subjected to privacy protection processing in the embodiment of the present specification may be a user image to be stored, where the user image may include one or more privacy information of a face, an iris, a fingerprint, a palm print, and the like of a user. For example, after passing biometric recognition based on the user image, the image processing apparatus determines a noise factor of the user image based on the current environment, and performs subsequent processing to store the user image in the form of an image file. The biometric identification process may be executed by the image processing apparatus, or may be executed by another identification device.

Step S104, generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance;

specifically, the noise factor of the specified user image is input to a generation model of the countermeasure noise obtained by performing a model training process in advance, and the generation process of the countermeasure noise is performed, and the generated countermeasure noise is output.

Step S106, carrying out superposition processing on the user image and the counternoise to obtain a target image;

in an embodiment, the pixel values of the same pixel points of the user image and the anti-noise image may be added according to the pixel points, the added pixel values are determined as the target pixel values of the corresponding pixel points, and the image corresponding to the target pixel values is determined as the target image. It should be noted that the manner of the superimposition processing is not limited to this manner, and it may be set by itself as needed in practical application, and this specification is not particularly limited.

And step S108, generating an image file according to the preset credible access information of the user image and the target image and saving the image file so as to carry out double verification processing on whether the target image has illegal access or not based on the saved image file when the preset verification condition is determined to be met.

The trusted access information may include device information of each trusted device having an access right of the target image, and an image file is generated based on the trusted access information and the target image, so that it is possible to perform a double verification process on whether there is an illegal access to the target image based on the image file. The process of generating the image file and the process of the double verification process can be referred to the related description below.

In one or more embodiments of the present description, a noise factor of a user image to be subjected to privacy protection processing is determined based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generated model of the counternoise obtained by performing model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. Moreover, the image file is generated based on the trusted access information and the target image, so that when the target image is accessed, double verification processing needs to be carried out on the access authority, the access legitimacy is further guaranteed, and the safety of the user privacy information is improved.

In order to improve the cracking difficulty of a target image generated based on the countermeasures against noise and limit the illegal access of the target image, in one or more embodiments of the present specification, an image processing apparatus determines a noise factor of a user image based on the current time and device information of a device where the image processing apparatus is currently located. Specifically, as shown in fig. 2, step S102 may include the following steps S102-2 to S102-6:

step S102-2, acquiring current time, and determining the current time as the last access time of a user image to be subjected to privacy protection processing;

step S102-4, acquiring the equipment identification of the first equipment where the equipment is located and the system information of the first equipment;

the device identifier may include a device serial number, a MAC address of the device, and the like; the system information may include a system type, a system version number, etc., for example, the system type is windows, the version number is 10, etc.

And step S102-6, determining the last access time, the equipment identifier and the system information as the noise factor of the user image.

Generating countermeasures noise by taking the last access time of the user image, the equipment identification of the current equipment and the system information as noise factors, thereby generating a target image; not only is the protection of the user image content realized, but also the target image can only be accessed in the trusted device corresponding to the noise factor, namely, the access control is increased. Even if the target image is stolen by a stealer, the stealer is difficult to acquire the noise factor, so that the stealer is difficult to attack the countermeasure noise, and the equipment of the stealer is not the credible equipment corresponding to the noise factor, so that the stealer cannot acquire the original content of the user image, and the safety protection of the user privacy information is realized.

In order to further improve the control of the access right of the target image, and ensure that the target image is only accessed in the trusted devices, in one or more embodiments of the present specification, the trusted access information includes a device identification list of each trusted device and a system information list of each trusted device. Accordingly, as shown in fig. 3, step S108 may include the following steps S108-2 to S108-6:

step S108-2, respectively carrying out coding processing on a preset equipment identification list of each trusted equipment, a preset system information list of each trusted equipment and the determined last access time by using a coder according to a preset coding mode to obtain a corresponding coding result;

specifically, in the embodiments of the present specification, the image processing apparatus is located in a set privacy protection system, the privacy protection system further includes an encoder, a decoder, and the like, and when the image processing apparatus generates an image file, the image processing apparatus performs encoding processing on the device identification list by using the encoder to obtain a first encoding result, performs encoding processing on the system information list to obtain a second encoding result, and performs encoding processing on the determined last access time to obtain a third encoding result. And when the target image is accessed, performing corresponding decoding processing by using a decoder, which can be specifically referred to in the related description below. The specific way of the encoding process includes, but is not limited to, performing the encoding process based on the Base64 encoding algorithm, which can be set by itself as required in practical application. It should be noted that the same encoding method may be used for encoding the device identifier list, the system information list, and the last access time, or different encoding methods may be used for encoding.

Step S108-6, generating check information according to the coding result;

the first encoding result, the second encoding result, and the third encoding result may be subjected to splicing processing, and the splicing result may be determined as the verification information. The generation mode of the verification information can be set in practical application according to needs, and it is ensured that each coding result can be obtained from the verification information in the process of accessing the target image, so that double verification processing is performed.

And S108-8, generating an image file according to the verification information and the target image and storing the image file.

In one embodiment, the image file may include two portions, a first portion for storing the verification information and a second portion for storing the target image. The target image may carry image information, such as an image identifier or an image name, and the image information may be obtained by performing, by the image processing apparatus, an allocation process according to a preset allocation manner before the target image is generated. The specific form of the image file is not specifically limited in this specification, and can be set by itself as needed in practical applications.

Therefore, the image file is generated according to the verification information and the target image, so that when the target image is accessed subsequently, the access environment can be verified based on the verification information, the access environment can also be verified based on the target image, illegal access can be avoided through double verification, and the privacy safety of a user is guaranteed. Specifically, as shown in fig. 4, step S108 may include the following step S110 and step S112:

step S110, if the preset verification condition is met, acquiring an image file of a target image to be verified;

and step S112, performing double verification processing on whether the target image to be verified has illegal access or not according to the acquired image file.

In one or more embodiments of the present specification, when the image processing apparatus receives the image access request, it is determined that the preset authentication condition is satisfied, specifically, as shown in fig. 5, step S110 may include the following step S110-2, and correspondingly, step S112 may include the following steps S112-2 and S112-4:

step S110-2, if the image access request is received, determining that a preset verification condition is met, determining an image to be accessed corresponding to the image access request as a target image to be verified, and acquiring an image file of the target image to be verified;

the image processing device determines that a preset verification condition is met when the image access request is received, determines an image corresponding to the image information in the image access request as a target image to be verified, and acquires corresponding image files from stored image files according to the image information in the image access request.

Step S112-2, according to the acquired image file, carrying out double verification processing on whether the target image to be verified has illegal access;

specifically, the verification information and the target image are obtained from the obtained image file; performing first verification processing according to the verification information, and performing second verification processing according to the target image; and if the first verification processing and the second verification processing are verified to pass, determining that the target image to be verified has no illegal access.

The performing the first verification process according to the verification information may include:

acquiring each coding result from the verification information; decoding each coding result by using a decoder to obtain an equipment identification list, a system information list and last access time; acquiring current time, and equipment identification and system information of current target equipment; determining whether the device identification list contains the device identification of the target device, determining whether the system information list contains the system information of the target device, and determining whether the last access time is earlier than the current time; and if the determination results are yes, determining that the verification result of the first verification processing is verification pass.

More specifically, the image processing apparatus acquires the first encoding result, the second encoding result, and the third encoding result from the verification information. The image processing device utilizes the decoder to decode the first coding result to obtain the device identification list of each credible device, utilizes the decoder to decode the second coding result to obtain the system information list of each credible device, and utilizes the encoder to decode the third coding result to obtain the last access time of the user image corresponding to the target image. The image processing device acquires the equipment identification and the system information of the current target equipment, determines whether the equipment identification list obtained by decoding contains the equipment identification of the target equipment, and if not, determines that the target image to be verified has illegal access and displays prompt information without access authority; if so, determining whether a system information list obtained by decoding contains system information of the target equipment, otherwise, determining that the target image to be verified has illegal access, and displaying prompt information without access authority; if so, determining whether the last access time obtained by decoding is earlier than the obtained current time, otherwise, determining that the target image to be verified has illegal access, and displaying prompt information without access authority; if yes, the verification result of the first verification processing is determined to be verification passing. The verification sequence of the device identifier of the target device, the system information, and the current time is not limited to the above sequence, and may be interchanged with each other. By performing the first authentication process, the first re-authentication of the access environment is realized.

Further, performing the second verification process according to the target image may include:

identifying the counternoise in the target image through a noise identification model obtained by performing model training in advance to obtain equipment identification, system information and last access time corresponding to the counternoise; determining whether the acquired device identification of the target device is matched with the device identification corresponding to the counternoise, determining whether the acquired system information of the target device is matched with the system information corresponding to the counternoise, and determining whether the last access time obtained by decoding is matched with the last access time corresponding to the counternoise; and if the determination results are yes, determining that the verification result of the second verification processing is verification pass.

More specifically, the image processing apparatus inputs the acquired target image into a noise recognition model obtained by performing model training processing in advance to perform recognition processing of anti-noise, and outputs a device identifier, system information, and last access time corresponding to the anti-noise. The image processing device determines whether the acquired equipment identification of the target equipment is matched with the equipment identification corresponding to the counternoise, if not, the target image to be verified is determined to have illegal access, and prompt information without access authority is displayed; if so, determining whether the acquired system information of the target equipment is matched with the system information corresponding to the counternoise, otherwise, determining that the target image to be verified has illegal access, and displaying prompt information without access authority; if so, determining whether the last access time obtained by decoding processing is matched with the last access time corresponding to the counternoise; if not, determining that the target image to be verified has illegal access, and displaying prompt information without access authority; if yes, the verification result of the second verification processing is determined to be verification passing. The verification sequence of the device identifier, the system information and the last access time corresponding to the anti-noise is not limited to the above verification sequence, and may be interchanged with each other. Through the second verification processing, the second verification of the access environment is realized, the illegal access caused by tampering the image file by a stealer is avoided, and the access effectiveness is improved.

In one or more embodiments of the present specification, the image processing apparatus may further acquire, by using a decoder, the verification information and the target image from the image file, and acquire the device identifier and the system information of the target device in which the image processing apparatus is currently located, and complete the aforementioned first authentication processing and second authentication processing.

It is understood that the image file in the present specification is in a set privacy protection system together with the image processing apparatus, the encoder, the decoder, the noise recognition model, and the like, and when a thief steals the image file, it is necessary to steal the associated image processing apparatus, decoder, and noise recognition model at the same time to perform the above-described first authentication process and second authentication process by the image processing apparatus, decoder, and noise recognition model when accessing the target image. It can be seen that the embodiment of the present specification not only achieves user privacy protection, but also increases the difficulty of a thief stealing an image.

And step S112-4, if the verification result of the double verification processing represents that the target image to be verified does not have illegal access, displaying the user image.

Therefore, when the image processing device receives the image access request, the access authority of the current target device is subjected to double verification processing based on the corresponding image file, so that illegal access can be effectively identified, and the security protection of the user privacy information is realized.

In order to further improve the security of the private information of the user, in one or more embodiments of the present specification, the image processing apparatus may further perform a double authentication process based on each saved image file according to a preset authentication period to check whether there is an illegal access to the image. Specifically, as shown in fig. 6, step S110 may include the following step S110-4 and step S110-6, and correspondingly, step S112 may include the following step S112-6 and step S112-8:

step S110-4, if the verification time corresponding to the preset verification period is determined to be reached, determining that the preset verification condition is met, and randomly extracting image files with preset proportion from the stored image files;

the duration and the preset ratio of the preset period can be set in practical application according to needs, for example, the preset duration is 24 hours, one week, etc., and the preset ratio is 1/2, 1/3, etc.

Step S110-6, determining the target image corresponding to the extracted image file as a target image to be verified;

step S112-6, according to each extracted image file, carrying out double verification processing on whether the corresponding target image to be verified has illegal access;

specifically, for each extracted image file, verification information and a target image to be verified are obtained from the image file; performing first verification processing according to the verification information, and performing second verification processing according to the target image; and if the first verification processing and the second verification processing are verified to pass, determining that the target image to be verified has no illegal access. The first verification process is performed according to the verification information, and the process of performing the second verification process according to the target image may refer to the foregoing related description, and repeated details are not repeated here.

And step S112-8, if the verification result of the double verification process indicates that the target image to be verified does not have illegal access, updating the target image to be verified and the image file thereof according to the verification time of the target image to be verified.

When the verification result of the double verification process indicates that the target image to be verified does not have illegal access, the image processing device can display the corresponding user image and simultaneously determine that the current target equipment is the first equipment when the target image to be verified is generated. Correspondingly, the updating the target image to be verified and the image file thereof according to the verification time of the target image to be verified may include: determining the verification time of a target image to be verified as the new last access time of a corresponding user image, determining the acquired device identification and system information of the first device and the determined new last access time as the new noise factor of the corresponding user image, generating a new anti-noise of the corresponding user image based on the new noise factor through a generated model of the anti-noise obtained by performing model training in advance; superposing the user image and the new countermeasure noise to obtain a new target image; and generating a new image file according to the preset credible access information of the user image and the new target image, deleting the extracted corresponding image file and saving the new image file. The process of generating a new image file is the same as the process of generating an image file, and reference may be made to the foregoing related description, which is not repeated herein.

Further, if the verification result of the double verification process indicates that the target image to be verified has illegal access, it may be determined that a period from the last access time corresponding to the anti-noise in the target image to the current verification time is a period in which the illegal access is located, and the tracing process of the illegal access may be performed according to the period. The specific mode of the tracing processing can be set in practical application according to the requirement.

In view of the fact that in practical applications, user images tend to have a requirement for transmission across devices, in one or more embodiments of the present specification, the method may further include:

if it is determined that the user image is to be transmitted from the first device where the user image is currently located to the second device, verifying whether the second device is a trusted device according to preset trusted access information of the user image; if so, updating the image file of the user image according to the determined equipment information of the second equipment; and sending the updated image file to the second device.

Specifically, when the image processing apparatus receives an image transmission instruction or an image acquisition request sent by the second device, the image processing apparatus acquires image information of a target image corresponding to a user image to be transmitted, an apparatus identifier of the second device, and system information from the image transmission instruction or the image acquisition request. The image processing device determines whether a preset device information list of each trusted device of the user image includes a device identifier of a second device, and determines whether a preset system information list of each trusted device of the user image includes system information of the second device; and if the determination result is yes, determining that the second equipment is the trusted equipment. The image processing device acquires a corresponding image file according to the acquired image information, performs double verification processing based on the acquired image file, and obtains a user figure to be transmitted after the verification is passed. The image processing device acquires current time, determines the acquired current time, the equipment identifier of the second equipment and system information as a new noise factor of the user image to be transmitted, generates a new counternoise of the user image to be transmitted based on the new noise factor through a counternoise generation model obtained by performing model training processing in advance; the user image to be transmitted and the new countermeasure noise are subjected to superposition processing to obtain a new target image; and generating a new image file according to the preset credible access information of the user image to be transmitted and the new target image, deleting the stored image file of the user image to be transmitted, and sending the new image file to the second equipment so as to realize cross-equipment transmission of the corresponding user image to be transmitted.

Therefore, the new image file is sent to the second equipment, so that the safety of the user privacy information is guaranteed, and the second equipment can access the corresponding user image based on the image processing device arranged in the second equipment.

In order to achieve generation of noise immunity and thus protect the privacy of the content of the user image, in one or more embodiments of the present specification, step S102 may further include the following step S100-2 and step S100-4:

s100-2, acquiring a training sample set; wherein the labeling data of each training sample in the training sample set comprises a first noise factor;

and S100-4, performing model training processing based on the training sample set, the pre-trained noise recognition model and a preset loss function to obtain a generation model of the counternoise.

Specifically, as shown in fig. 7, step S100-4 may include the following steps S100-4-2 to S100-4-10:

step S100-4-2, iteratively inputting a training sample set into a network to be trained for training, and outputting counternoise generated based on a noise factor;

specifically, the training sample set may be divided into a plurality of training subsets according to a preset dividing manner, each training subset is input into the network to be trained for training, and the counternoise generated based on the first noise factor corresponding to each training sample in the training subsets is output.

S100-4-4, performing superposition processing on the counternoise and the corresponding training sample to obtain a target training sample;

the implementation of this step is the same as that of the step S106, and reference may be made to the related description.

S100-4-6, identifying and processing the counternoise in the target training sample through a pre-trained noise identification model to obtain a corresponding second noise factor;

the noise recognition model may be an OCR model, and the training mode of the noise recognition model may refer to the existing model training mode, which is not limited in this specification.

S100-4-8, calculating a loss value based on the training sample, the target training sample, the first noise factor and the second noise factor according to a preset loss function; the loss function is used for restraining the difference degree of the visual effects of the training samples and the corresponding target training samples to be smaller than a first threshold value, and restraining the difference degree of the first noise factor and the second noise factor to be smaller than a second threshold value;

wherein the loss function can be expressed as: l is_total＝L_norm(N)+L_ocr(O,I)；L_totalFor characterizing total loss, N for countering noise, L_norm(N) for constraining the training samples to be substantially identical in visual effect with target training samples obtained by superimposing the training samples against the noise, that is, the degree of difference in visual effect is smaller than a first threshold; o denotes the second noise factor, I denotes the first noise factor, L_ocr(O, I) for constraining the first noise factor to be as consistent as possible with the second noise factor, i.e. the first noise factor and the second noise factorThe degree of difference in acoustic factors is less than a second threshold. The degree of difference can be determined by calculating the euclidean distance, etc.

And S100-4-10, performing tuning treatment on the network to be trained according to the loss value until a preset training end condition is met, and obtaining a generation model of the counternoise.

The network to be trained may be a pnet network or the like. Compared with the existing encryption algorithm, the process of generating the counternoise by the generation model is much more complex, so that the counternoise generated based on the generation model is generated, and the target image is generated based on the counternoise, so that the target image is more difficult to break compared with the image encrypted by the encryption algorithm, namely, the breaking difficulty is increased, and the risk of user privacy disclosure is favorably reduced.

In one or more embodiments of the present description, a noise factor of a user image to be subjected to privacy protection processing is determined based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. Moreover, the image file is generated based on the trusted access information and the target image, so that when the target image is accessed, double verification processing needs to be carried out on the access authority, the access legitimacy is further guaranteed, and the safety of the user privacy information is improved.

Corresponding to the image processing method based on privacy protection described above, based on the same technical concept, one or more embodiments of the present specification further provide another image processing method based on privacy protection, and fig. 8 is a flowchart of another image processing method based on privacy protection provided by one or more embodiments of the present specification. The method of fig. 8 can be performed by an image processing apparatus based on privacy protection, which may be deployed in a blockchain system, and more specifically, may be deployed in a blockchain node in the blockchain system. As shown in fig. 8, the method comprises the steps of:

step S202, determining a noise factor of a user image to be subjected to privacy protection processing based on the current environment;

step S204, generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance;

step S206, the user image and the counternoise are subjected to superposition processing based on the intelligent contract in the block chain system to obtain a target image;

specifically, an intelligent contract deployed in a block chain system is called, pixel values of the same pixel points of the user image and the counternoise are added according to the pixel points based on the intelligent contract, the pixel values after the addition are determined as target pixel values of the corresponding pixel points, and an image corresponding to the target pixel values is determined as a target image.

Step S208, generating an image file according to the preset credible access information of the user image and the target image based on the intelligent contract;

specifically, the trusted access information includes a device identifier list of each trusted device and a system information list of each trusted device; respectively coding the equipment identification list, the system information list and the determined last access time of the user image according to a preset coding mode based on an intelligent contract to obtain a corresponding coding result; generating check information according to the coding result; and generating an image file according to the verification information and the target image.

It should be noted that the intelligent contract in step S206 and the intelligent contract in step S208 may be the same intelligent contract, or may be different intelligent contracts, which may be set by themselves in practical applications as needed.

Step S210, saving the image file into the blockchain system, so as to perform a double verification process on whether the target image has an illegal access based on the image file in the blockchain system when it is determined that the preset verification condition is satisfied.

The implementation manners of some operations in step S202 to step S210 may refer to the foregoing related descriptions, and the description is omitted here.

In one or more embodiments of the present specification, a noise factor of a user image to be subjected to privacy protection processing is determined based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing a user image and counternoise based on an intelligent contract in a block chain system to obtain a target image; and generating an image file according to the preset trusted access information of the user image and the target image based on the intelligent contract and storing the image file into the block chain system. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. By generating the image file based on the trusted access information and the target image, when the target image is accessed, the access authority needs to be subjected to double verification processing, so that the access validity is further ensured, and the safety of the user privacy information is improved. Moreover, the target images and the image files are generated based on the intelligent contract, the generation efficiency of the target images and the image files can be improved based on the characteristics of automatic execution, no human intervention and the like of the intelligent contract, and the accuracy is guaranteed. By storing the image file into the block chain system, the authenticity and the validity of the image file can be guaranteed based on the characteristics of the block chain system, such as public transparency and incapability of tampering, so that an effective verification basis is provided for subsequent double verification processing.

In correspondence to the image processing method based on privacy protection described above, based on the same technical concept, one or more embodiments of the present specification further provide an image processing apparatus based on privacy protection. Fig. 9 is a schematic block diagram of an image processing apparatus based on privacy protection according to one or more embodiments of the present specification, where, as shown in fig. 9, the apparatus includes:

a determining module 301, configured to determine a noise factor of a user image to be subjected to privacy protection processing based on a current environment;

a first generation module 302 that generates a noise countermeasure for the user image based on the noise factor by using a noise countermeasure generation model obtained by performing a model training process in advance;

the superposition module 303 is used for carrying out superposition processing on the user image and the countermeasure noise to obtain a target image;

the second generating module 304 generates and stores an image file according to the preset trusted access information of the user image and the target image, so as to perform double verification processing on whether the target image has illegal access based on the stored image file when it is determined that a preset verification condition is met.

Optionally, the determining module 301 obtains a current time, and determines the current time as a last access time of the user image; and the number of the first and second groups,

acquiring a device identifier of a first device where the first device is located and system information of the first device;

determining the last access time, the device identification, and the system information as a noise factor for the user image.

Optionally, the trusted access information includes a device identification list of each trusted device and a system information list of the trusted device;

correspondingly, the second generating module 304 encodes the device identifier list, the system information list and the last access time by using an encoder according to a preset encoding mode to obtain corresponding encoding results; and the number of the first and second groups,

generating check information according to the coding result;

and generating an image file according to the verification information and the target image.

Optionally, the apparatus further includes a verification module, where the verification module acquires the image file of the target image to be verified if it is determined that a preset verification condition is met; and the number of the first and second groups,

and performing double verification processing on whether the target image to be verified has illegal access or not according to the acquired image file.

The image processing device based on privacy protection provided by one or more embodiments of the present specification determines a noise factor of a user image to be subjected to privacy protection processing based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. Moreover, the image file is generated based on the trusted access information and the target image, so that when the target image is accessed, double verification processing needs to be carried out on the access authority, the access legitimacy is further guaranteed, and the safety of the user privacy information is improved.

Further, in correspondence to the image processing method based on privacy protection described above, based on the same technical concept, one or more embodiments of the present specification further provide another image processing apparatus based on privacy protection. Fig. 10 is a schematic block diagram of another image processing apparatus based on privacy protection according to one or more embodiments of the present disclosure, where as shown in fig. 10, the apparatus includes:

the determining module 401 determines a noise factor of a user image to be subjected to privacy protection processing based on a current environment;

a first generation module 402 that generates the countermeasure noise of the user image based on the noise factor by a generation model of the countermeasure noise obtained by performing a model training process in advance;

the overlapping module 403 is configured to perform overlapping processing on the user image and the countermeasure noise based on an intelligent contract in the block chain system to obtain a target image;

a second generating module 404, configured to generate an image file according to preset trusted access information of the user image and the target image based on the smart contract;

the saving module 405 saves the image file into the blockchain system, so as to perform a double verification process on whether the target image has an illegal access based on the image file in the blockchain system when it is determined that a preset verification condition is met.

correspondingly, the second generating module 404 is configured to encode the device identifier list, the system information list and the last access time according to a preset encoding mode based on the intelligent contract, so as to obtain corresponding encoding results; generating check information according to the coding result; and generating an image file according to the verification information and the target image.

The image processing device based on privacy protection provided by one or more embodiments of the present specification determines a noise factor of a user image to be subjected to privacy protection processing based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing a user image and counternoise based on an intelligent contract in a block chain system to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image based on the intelligent contract and storing the image file into the block chain system. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. By generating the image file based on the trusted access information and the target image, when the target image is accessed, the access authority needs to be subjected to double verification processing, so that the access validity is further ensured, and the safety of the user privacy information is improved. Moreover, the target images and the image files are generated based on the intelligent contract, the generation efficiency of the target images and the image files can be improved based on the characteristics of automatic execution, no human intervention and the like of the intelligent contract, and the accuracy is guaranteed. By storing the image file into the block chain system, the authenticity and the validity of the image file can be guaranteed based on the characteristics of the block chain system, such as public transparency and incapability of tampering, so that an effective verification basis is provided for subsequent double verification processing.

It should be noted that, the embodiment of the image processing apparatus based on privacy protection in this specification and the embodiment of the image processing method based on privacy protection in this specification are based on the same inventive concept, and therefore, specific implementation of this embodiment may refer to implementation of the corresponding image processing method based on privacy protection, and repeated details are omitted.

Further, corresponding to the image processing method based on privacy protection described above, based on the same technical concept, one or more embodiments of the present specification further provide an image processing apparatus based on privacy protection, where the apparatus is configured to execute the image processing method based on privacy protection described above, and fig. 11 is a schematic structural diagram of an image processing apparatus based on privacy protection provided in one or more embodiments of the present specification.

As shown in fig. 11, the image processing apparatus based on privacy protection may have a relatively large difference due to different configurations or performances, and may include one or more processors 501 and a memory 502, where the memory 502 may store one or more stored applications or data. Memory 502 may be, among other things, transient or persistent storage. The application programs stored in memory 502 may include one or more modules (not shown), each of which may include a series of computer-executable instructions in a privacy-based image processing apparatus. Still further, the processor 501 may be configured to communicate with the memory 502 to execute a series of computer-executable instructions in the memory 502 on a privacy-based image processing device. The privacy-based image processing apparatus may also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input-output interfaces 505, one or more keyboards 506, and the like.

In a particular embodiment, a privacy-based image processing apparatus includes a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the privacy-based image processing apparatus, and execution of the one or more programs by one or more processors includes computer-executable instructions for:

determining a noise factor of a user image to be subjected to privacy protection processing based on the current environment;

generating the counternoise of the user image based on the noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance;

superposing the user image and the confrontation noise to obtain a target image;

and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met.

Optionally, when executed, the computer-executable instructions determine a noise factor of the user image to be subjected to privacy protection processing based on the current environment, including:

acquiring current time, and determining the current time as the last access time of the user image;

Optionally, when executed, the trusted access information includes a device identification list of each trusted device and a system information list of the trusted device;

the generating an image file according to the preset credible access information of the user image and the target image comprises the following steps:

respectively coding the equipment identification list, the system information list and the last access time by using a coder according to a preset coding mode to obtain corresponding coding results;

generating check information according to the coding result;

The image processing device based on privacy protection provided by one or more embodiments of the present specification determines, based on a current environment, a noise factor of a user image to be subjected to privacy protection processing; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. Moreover, the image file is generated based on the trusted access information and the target image, so that when the target image is accessed, double verification processing needs to be carried out on the access authority, the access legitimacy is further guaranteed, and the safety of the user privacy information is improved.

In another particular embodiment, a privacy-based image processing apparatus includes a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the privacy-based image processing apparatus, and execution of the one or more programs by one or more processors includes computer-executable instructions for:

superposing the user image and the counternoise based on an intelligent contract in a block chain system to obtain a target image;

generating an image file according to preset credible access information of the user image and the target image based on the intelligent contract;

and saving the image file to the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file is determined to meet the preset verification condition.

The image processing device based on privacy protection provided by one or more embodiments of the present specification determines, based on a current environment, a noise factor of a user image to be subjected to privacy protection processing; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing a user image and counternoise based on an intelligent contract in a block chain system to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image based on the intelligent contract and storing the image file into the block chain system. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. By generating the image file based on the trusted access information and the target image, when the target image is accessed, the access authority needs to be subjected to double verification processing, so that the access validity is further ensured, and the safety of the user privacy information is improved. Moreover, the target images and the image files are generated based on the intelligent contract, the generation efficiency of the target images and the image files can be improved based on the characteristics of automatic execution, no human intervention and the like of the intelligent contract, and the accuracy is guaranteed. By storing the image file into the block chain system, the authenticity and the validity of the image file can be guaranteed based on the characteristics of the block chain system, such as public transparency and incapability of tampering, so that an effective verification basis is provided for subsequent double verification processing.

It should be noted that, the embodiment of the image processing apparatus based on privacy protection in this specification and the embodiment of the image processing method based on privacy protection in this specification are based on the same inventive concept, and therefore, for specific implementation of this embodiment, reference may be made to implementation of the corresponding image processing method based on privacy protection, and repeated details are not repeated.

Further, corresponding to the image processing method based on privacy protection described above, based on the same technical concept, one or more embodiments of the present specification further provide a storage medium for storing computer-executable instructions, where in a specific embodiment, the storage medium may be a usb disk, an optical disk, a hard disk, and the like, and the storage medium stores computer-executable instructions that, when executed by a processor, implement the following processes:

Optionally, the storage medium stores computer executable instructions, which when executed by the processor, determine a noise factor of an image of a user to be subjected to privacy protection processing based on a current environment, and includes:

Optionally, the storage medium stores computer-executable instructions that, when executed by the processor, cause the trusted access information to include a list of device identifications of trusted devices and a list of system information of the trusted devices;

the generating of the image file according to the preset credible access information of the user image and the target image comprises the following steps:

generating check information according to the coding result;

One or more embodiments of the present description provide a storage medium storing computer-executable instructions that, when executed by a processor, determine a noise factor for a user image to be privacy-protected based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing the user image and the counternoise to obtain a target image; and generating an image file according to the preset credible access information of the user image and the target image and storing the image file so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. Moreover, the image file is generated based on the trusted access information and the target image, so that when the target image is accessed, double verification processing needs to be carried out on the access authority, the access legitimacy is further guaranteed, and the safety of the user privacy information is improved.

In another specific embodiment, the storage medium may be a usb disk, an optical disk, a hard disk, or the like, and the storage medium stores computer executable instructions that, when executed by the processor, implement the following process:

and saving the image file into the blockchain system so as to perform double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the image file is determined to meet the preset verification condition.

One or more embodiments of the present description provide a storage medium storing computer-executable instructions that, when executed by a processor, determine a noise factor for a user image to be privacy-protected based on a current environment; generating the counternoise of the user image based on the determined noise factor through a generation model of the counternoise obtained by carrying out model training processing in advance; superposing a user image and counternoise based on an intelligent contract in a block chain system to obtain a target image; and generating an image file according to the preset trusted access information of the user image and the target image based on the intelligent contract and storing the image file into the block chain system. Therefore, the noise factor is determined based on the current environment, the counternoise is generated based on the generation model, the target image comprising the counternoise is generated, the content protection of the original user image is realized, and the cracking difficulty and the access limitation are increased. By generating the image file based on the trusted access information and the target image, when the target image is accessed, the access authority needs to be subjected to double verification processing, so that the access validity is further ensured, and the safety of the user privacy information is improved. Moreover, the target images and the image files are generated based on the intelligent contract, the generation efficiency of the target images and the image files can be improved based on the characteristics of automatic execution, no human intervention and the like of the intelligent contract, and the accuracy is guaranteed. By storing the image file into the block chain system, the authenticity and the validity of the image file can be guaranteed based on the characteristics of the block chain system, such as public transparency and incapability of tampering, so that an effective verification basis is provided for subsequent double verification processing.

It should be noted that, the embodiment of the storage medium in this specification and the embodiment of the image processing method based on privacy protection in this specification are based on the same inventive concept, and therefore, specific implementation of this embodiment may refer to implementation of the aforementioned corresponding image processing method based on privacy protection, and repeated details are not repeated.

The foregoing description of specific embodiments has been presented for purposes of illustration and description. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to the software compiler used in program development, but the original code before compiling is also written in a specific Programming Language, which is called Hardware Description Language (HDL), and the HDL is not only one kind but many kinds, such as abel (advanced boot Expression Language), ahdl (alternate Language Description Language), communication, CUPL (computer universal Programming Language), HDCal (Java Hardware Description Language), langa, Lola, mylar, HDL, PALASM, rhydl (runtime Description Language), vhjhdul (Hardware Description Language), and vhygl-Language, which are currently used commonly. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: the ARC625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be regarded as a hardware component and the means for performing the various functions included therein may also be regarded as structures within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in multiple software and/or hardware when implementing the embodiments of the present description.

One skilled in the art will recognize that one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of this document and is not intended to limit this document. Various modifications and changes may occur to those skilled in the art from this document. Any modifications, equivalents, improvements, etc. which come within the spirit and principle of the disclosure are intended to be included within the scope of the claims of this document.

Claims

1. An image processing method based on privacy protection comprises the following steps:

generating the counternoise of the user image based on the noise factor through a generation model of the counternoise obtained by performing model training processing in advance;

2. The method of claim 1, wherein determining the noise factor of the user image to be subjected to privacy protection processing based on the current environment comprises:

3. The method of claim 2, the trusted access information comprising a list of device identifications of trusted devices and a list of system information of the trusted devices;

generating check information according to the coding result;

4. The method of claim 3, after generating and saving an image file according to the preset trusted access information of the user image and the target image, further comprising:

if an image access request is received, determining that the verification condition is met, and determining an image to be accessed corresponding to the image access request as a target image to be verified;

acquiring the image file of the target image to be verified;

according to the acquired image file, performing double verification processing on whether the target image to be verified has illegal access or not;

and if the verification result of the double verification processing represents that the target image to be verified has no illegal access, displaying the user image.

5. The method of claim 1 or 4, further comprising:

if the verification time corresponding to the preset verification period is determined to be reached, determining that the verification condition is met, and randomly extracting image files with preset proportions from each stored image file;

determining the target image corresponding to the extracted image file as a target image to be verified;

according to each extracted image file, performing double verification processing on whether the corresponding target image to be verified has illegal access or not;

and if the target image to be verified is represented to have no illegal access according to the verification result of the extracted image file subjected to the double verification processing, updating the target image to be verified and the image file thereof according to the verification time of the target image to be verified.

6. The method according to claim 4, wherein performing a double verification process on whether the target image to be verified has an illegal access according to the acquired image file comprises:

acquiring the verification information and the target image from the image file;

performing first verification processing according to the verification information;

performing second verification processing according to the target image;

and if the first verification processing and the second verification processing are verified to pass, determining that the target image to be verified has no illegal access.

7. The method of claim 6, the performing a first verification process based on the verification information comprising:

acquiring each coding result from the verification information;

decoding each coding result by using a decoder to obtain the equipment identification list, the system information list and the last access time;

acquiring current time, and equipment identification and system information of current target equipment;

determining whether the device identification list contains the device identification of the target device;

determining whether the system information list contains the system information of the target device;

determining whether the last access time is earlier than the current time;

and if the determination results are yes, determining that the verification result of the first verification processing is verification pass.

8. The method of claim 7, the performing a second verification process from the target image, comprising:

identifying the counternoise in the target image through a noise identification model obtained by performing model training in advance to obtain equipment identification, system information and last access time corresponding to the counternoise;

determining whether the acquired device identification of the target device is matched with the device identification corresponding to the countermeasure noise;

determining whether the acquired system information of the target device is matched with the system information corresponding to the countermeasure noise;

determining whether the last access time obtained by decoding is matched with the last access time corresponding to the countermeasures against noise;

and if the determination results are yes, determining that the verification result of the second verification processing is verification pass.

9. The method of claim 1, further comprising:

if the user image is determined to be transmitted from the first equipment where the user image is located to the second equipment, verifying whether the second equipment is the trusted equipment or not according to the trusted access information;

if yes, updating the image file according to the determined equipment information of the second equipment;

and sending the updated image file to the second device.

10. The method of claim 1, prior to determining a noise factor for a user image to be privacy preserving processed, the method further comprising:

acquiring a training sample set; the labeling data of each training sample in the set of training samples comprises a first noise factor;

iteratively inputting the training sample set into a network to be trained for training, and outputting the confrontation noise generated based on the first noise factor;

overlapping the confrontation noise and the corresponding training sample to obtain a target training sample;

identifying the counternoise in the target training sample through a pre-trained noise identification model to obtain a corresponding second noise factor;

calculating a loss value based on the training sample, the target training sample, the first noise factor, and the second noise factor according to a preset loss function; the loss function is used for restricting the difference degree of the visual effects of the training samples and the target training samples to be smaller than a first threshold value and restricting the difference degree of the first noise factor and the second noise factor to be smaller than a second threshold value;

and carrying out tuning treatment on the network to be trained according to the loss value until a preset training end condition is met, and obtaining the generation model of the counternoise.

11. An image processing method based on privacy protection comprises the following steps:

12. The method of claim 11, the trusted access information comprising a list of device identifications of trusted devices and a list of system information of the trusted devices;

the generating of the image file according to the preset credible access information of the user image and the target image based on the intelligent contract comprises the following steps:

respectively coding the equipment identification list, the system information list and the last access time based on the intelligent contract according to a preset coding mode to obtain corresponding coding results; generating check information according to the coding result; and generating an image file according to the verification information and the target image.

13. An image processing apparatus based on privacy protection, comprising:

the determining module is used for determining the noise factor of the user image to be subjected to privacy protection processing based on the current environment;

a first generation module, which generates the confrontation noise of the user image based on the noise factor through a generation model of the confrontation noise obtained by carrying out model training processing in advance;

the superposition module is used for carrying out superposition processing on the user image and the confrontation noise to obtain a target image;

and the second generation module is used for generating and storing an image file according to preset credible access information of the user image and the target image so as to perform double verification processing on whether the target image has illegal access or not based on the stored image file when the preset verification condition is determined to be met.

14. An image processing apparatus based on privacy protection, comprising:

the superposition module is used for carrying out superposition processing on the user image and the counternoise based on an intelligent contract in the block chain system to obtain a target image;

the second generation module is used for generating an image file according to preset credible access information of the user image and the target image based on the intelligent contract;

and the storage module is used for storing the image file into the blockchain system so as to carry out double verification processing on whether the target image has illegal access or not based on the image file in the blockchain system when the preset verification condition is determined to be met.

15. An image processing apparatus based on privacy protection, comprising:

a processor; and the number of the first and second groups,

a memory arranged to store computer executable instructions that, when executed, cause the processor to:

16. An image processing apparatus based on privacy protection, comprising:

a processor; and the number of the first and second groups,

17. A storage medium storing computer-executable instructions that when executed by a processor implement the following:

18. A storage medium storing computer-executable instructions that when executed by a processor implement the following: