CN113486377A - Image encryption method and device, electronic equipment and readable storage medium - Google Patents
Image encryption method and device, electronic equipment and readable storage medium Download PDFInfo
- Publication number
- CN113486377A CN113486377A CN202110830378.4A CN202110830378A CN113486377A CN 113486377 A CN113486377 A CN 113486377A CN 202110830378 A CN202110830378 A CN 202110830378A CN 113486377 A CN113486377 A CN 113486377A
- Authority
- CN
- China
- Prior art keywords
- image
- noise
- generate
- moire
- mask
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000012545 processing Methods 0.000 claims abstract description 30
- 238000004422 calculation algorithm Methods 0.000 claims description 21
- 230000009466 transformation Effects 0.000 claims description 15
- 238000007499 fusion processing Methods 0.000 claims description 6
- 230000003042 antagnostic effect Effects 0.000 claims description 2
- 230000011218 segmentation Effects 0.000 claims description 2
- 230000000694 effects Effects 0.000 description 20
- 239000011159 matrix material Substances 0.000 description 18
- 230000008569 process Effects 0.000 description 10
- 238000013473 artificial intelligence Methods 0.000 description 8
- 230000000007 visual effect Effects 0.000 description 7
- 238000004891 communication Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 239000000654 additive Substances 0.000 description 3
- 230000000996 additive effect Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000007635 classification algorithm Methods 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 206010047571 Visual impairment Diseases 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 230000000153 supplemental effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
- 230000016776 visual perception Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Bioethics (AREA)
- General Health & Medical Sciences (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Image Processing (AREA)
Abstract
The embodiment of the application provides an image encryption method and device, electronic equipment and a readable storage medium, and belongs to the technical field of image processing. The image encryption method comprises the following steps: determining a target area where to-be-encrypted content in an original image to be encrypted is located; performing mask processing on the target area, and determining mask information of the target area; adding counternoise and auxiliary noise on the original image to generate a noise image; and fusing the original image, the noise image and the mask information to generate a target encrypted image.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image encryption method and apparatus, an electronic device, and a readable storage medium.
Background
With the continuous development of the current mobile internet terminal equipment, more and more information exchange depends on the transmission of the terminal equipment. When a user shoots screen content on a screen of a terminal device by others or acquires a real-time display picture of the screen by a malicious application on the terminal, a lot of privacy data of the user is leaked through a screen image.
In the related technology, aiming at the encryption of the terminal image, some secret keys are used for encrypting the image, so that the safety is low, and the encryption methods are often easy to crack by artificial intelligence technology. Some of the images are enhanced in security by setting a different key for each image, but the workload is large, and a large burden is brought to the calculation and storage of the system.
Disclosure of Invention
The embodiment of the application provides an image encryption method and device, electronic equipment and a readable storage medium, which can enable an encrypted screen image to resist malicious programs and prevent the malicious programs from reading user information.
In a first aspect, an embodiment of the present application provides an image encryption method, including:
determining a target area where to-be-encrypted content in an original image to be encrypted is located;
performing mask processing on the target area, and determining mask information of the target area;
adding counternoise and auxiliary noise on the original image to generate a noise image;
and fusing the original image, the noise image and the mask information to generate a target encrypted image.
In a second aspect, an embodiment of the present application provides an image encryption apparatus, including:
the determining module is used for determining a target area where the content to be encrypted in the original image to be encrypted is located;
the mask module is used for performing mask processing on the target area and determining mask information of the target area;
the noise adding module is used for adding counternoise and auxiliary noise on the original image to generate a noise image;
and the generating module is used for carrying out fusion processing on the original image, the noise image and the mask information to generate a target encrypted image.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instructions stored on the memory and executed on the processor, where the program or instructions, when executed by the processor, implement the steps of the image encryption method as provided in the first aspect.
In a fourth aspect, the present application provides a readable storage medium, on which a program or instructions are stored, which when executed by a processor implement the steps of the image encryption method as provided in the first aspect.
In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement the steps of the image encryption method as provided in the first aspect.
In the embodiment of the application, a target area where the content to be encrypted in the original image to be encrypted is located is determined; performing mask processing on the target area, and determining mask information of the target area; adding counternoise and auxiliary noise on the original image to generate a noise image; and fusing the original image, the noise image and the mask information to generate a target encrypted image. Therefore, the anti-noise and auxiliary noise contained in the target encrypted image are utilized to interfere the image information on which the image identification algorithm depends, so that the image identification fails, the encryption of the image is realized, the encryption effect is ensured, different keys do not need to be set for different images, the requirements on the calculation and storage of the system are greatly reduced, and the security and the efficiency of the image encryption are improved.
Drawings
FIG. 1 shows one of the flow diagrams of an image encryption method according to one embodiment of the present application;
FIG. 2 shows a second flowchart of an image encryption method according to an embodiment of the present application;
FIG. 3 shows a third flowchart of an image encryption method according to an embodiment of the present application;
FIG. 4 shows a fourth flowchart of an image encryption method according to one embodiment of the present application;
FIG. 5 shows a fifth flowchart of an image encryption method according to an embodiment of the present application;
FIG. 6 shows six of a flow chart of an image encryption method according to one embodiment of the present application;
FIG. 7 shows a seventh flowchart of an image encryption method according to an embodiment of the present application;
FIG. 8 illustrates an electronic device display diagram according to one embodiment of the present application;
fig. 9 shows a block diagram of the structure of an image encryption apparatus according to an embodiment of the present application;
FIG. 10 shows a block diagram of an electronic device according to an embodiment of the present application;
fig. 11 shows a block diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present disclosure.
The terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one. In addition, "and/or" in the specification and claims means at least one of connected objects, a character "/" generally means that a preceding and succeeding related objects are in an "or" relationship.
An image encryption method, an image encryption apparatus, an electronic device, and a readable storage medium according to some embodiments of the present application are described below with reference to fig. 1 to 11.
In an embodiment of the present application, fig. 1 shows one of flowcharts of an image encryption method of the embodiment of the present application, including:
in this embodiment, encryption refers to encrypting an original Image, so that it is difficult for an artificial intelligence Image recognition algorithm based on the ResNet structure to analyze the content of an Image display, the EXIF (Exchangeable Image File) information of the Image, and the like.
The original image may be a screen image currently displayed by an item of the electronic device, may also be an image opened by the album application when receiving a request to view the image, and may also be a picture captured from a photo or a video by shooting according to a shooting operation triggered by a user, which is not limited in the embodiment of the present application. The content to be encrypted is content which may contain user privacy and needs to be encrypted. The content to be encrypted includes: text, graphics, symbols, charts, etc.
Further, in the case of having a plurality of original images, before encryption, the original images may be subjected to size normalization processing to unify the size of the images, so as to facilitate batch encryption of the plurality of original images. For example, the original image is converted into an image of 256 × 256 size. The step of processing the image not only comprises screening and size normalization, but also comprises a plurality of image processing steps such as brightness adjustment, definition adjustment, contrast adjustment, gray level adjustment, mirror image, sharpening and the like so as to accurately determine the target area.
104, performing mask processing on the target area to determine mask information of the target area;
in this embodiment, by performing mask processing on the target area, mask information (mask) of the target area is determined to mark a position where the content to be encrypted is located in the original image with the mask information, so as to individually encrypt the content to be encrypted in the original image. Therefore, in the encryption process, specific information in the content to be encrypted does not need to be identified, and the encryption processing of the specified content can be realized only by determining the position of the target area of the content to be encrypted.
Wherein the mask information is an integer matrix of an original image size, and element values of the matrix include 0 or 1.
the anti-noise is additive noise which does not affect visual appearance and is added to the image, the anti-noise is anti (additive) disturbance, the classification capability of a machine learning model can be effectively reduced, most of images added with the anti-noise are wrongly classified, the effect of disturbing data points is achieved, accordingly, under the condition that the visual perception of a person is not affected, the image information depended by an image recognition algorithm is interfered, and the images are prevented from being recognized and crawled by the recognition algorithm. The auxiliary noise includes moir e noise and/or random noise. Moire is a high frequency interference that occurs with light sensing elements on devices such as digital cameras or scanners, which causes the image to appear as a colored high frequency streak. Since the moire pattern is irregular, there is no apparent regularity in shape. Generally, the moire pattern generated when photographing is in the form of concentric circles to form a plurality of circular rings. Random noise, also known as background noise, refers to unnecessary or unwanted interference information present in the image data, accumulated from a large number of fluctuating perturbations that are randomly generated in time, and is noise that cannot be predicted at a given instant.
In this embodiment, the noise image includes a contrast noise image and a supplemental noise image, which in turn includes a moire noise image and/or a random noise image. Because the anti-noise has small visual disturbance on the image, although the attack of an intelligent recognition algorithm can be resisted, the information leakage caused by manual checking cannot be prevented. For this reason, an auxiliary noise is further added to the original image on the basis of the addition of the countermeasure noise, and the "occlusion" effect is added to the original image by the auxiliary noise. The content in the original image can not be completely displayed by the target encrypted image, so that information leakage caused by visual recognition can be prevented, the denoising effect of an artificial intelligence algorithm can be further interfered, and the encryption effect of the original image is improved.
And step 108, fusing the original image, the noise image and the mask information to generate a target encrypted image.
In this embodiment, the above-described noise image, original image, and mask information are subjected to signal-to-noise fusion processing to encrypt the content to be encrypted in the original image using the noise image as an encryption key, so that the fused target encrypted image contains both the counternoise and the auxiliary noise. Therefore, the anti-noise effect contained in the target encryption image interferes with the image information depended by the image identification algorithm, meanwhile, the auxiliary noise is utilized to achieve the effect of shielding the content to be encrypted in the original image, the interference to the image identification algorithm is enhanced, the image identification fails, the image encryption is achieved, the privacy of a user is protected from being leaked, different secret keys do not need to be set aiming at different images, the requirements for calculation and storage of a system are greatly reduced, and the safety and efficiency of the image encryption are improved. Meanwhile, the position of the non-target area in the target encrypted image can also present a visual effect similar to that of the original image, so that non-privacy information in the original image is kept as much as possible, and convenience for users to look up can be taken into account on the basis of preventing privacy disclosure.
Further, the target encrypted image may be directly output to an output device of the electronic apparatus for transmission or display.
It can be understood that the essence of the fusion of the original image and the noisy image is the superposition of the image pixel matrices.
In particular, the image encryption method is suitable for electronic devices including, but not limited to, mobile terminals, tablet computers, notebook computers, wearable devices, vehicle-mounted terminals, and the like.
In one embodiment of the present application, the noise image includes a contrast noise image and an auxiliary noise image; as shown in fig. 2, step 108, performing fusion processing on the original image, the noise image and the mask information to generate a target encrypted image, includes:
step 204, performing element-corresponding product operation on the auxiliary noise image and the mask information to generate a second image;
wherein the elements correspond to product operations (elemen)t-wise entrywise product), i.e. the product of corresponding elements in two matrices of the same dimension, also called Hadamard product. Specifically, the hadamard product of the two m × n matrices a and B is defined as: element a of matrix AijCorresponding element B to matrix BijProduct of aij×bijThe resulting m × n matrix C. Wherein i is 1, 2, …, m; j is 1, 2, …, n. Since the anti-noise image and the auxiliary noise image are obtained based on the original image, the anti-noise image and the auxiliary noise image each have a matrix of the same size with the dimension of the original image, and the anti-noise image, the auxiliary noise image and the original image can be subjected to element-corresponding product operation with each other.
And step 206, performing superposition operation on the first image and the second image according to the first preset weight to generate a target encrypted image.
The first preset weight is used for indicating the ratio of the first image to the second image in the superposition operation. The first image and the second image are subjected to superposition operation, namely C ═ a × a + B × B, a and B are first preset weights, C is a matrix of the target encrypted image, a is a matrix of the first image, and B is a matrix of the second image. a can be the same as b, a and b can also be different, and the first preset weight can be reasonably set according to the encryption requirement of the user. For example, a is set to 0.5, i.e. the matrix element value of the first image is multiplied by 0.5 in the superposition operation. In the case where the auxiliary noise image includes a moire noise image and a random noise image, that is, the second image includes two images, the two images are matrix-added to the first image, and the first preset weight (a, b1, b2) of each image is set to 0.33, then the matrix pixel value of each image is one third each at the time of performing the superposition operation, that is, the matrix pixel value of the target encrypted image is the average value of the matrix pixel values of the two images included in the second image and the first image.
In this embodiment, a first image to which the anti-noise disturbance is added is obtained by performing a superposition operation on the original image and the anti-noise image, and a second image to which the auxiliary noise is added to the target region is obtained by performing an element-corresponding product operation on the auxiliary noise image and the mask information. And finally, according to the first preset weight, performing superposition operation on the first image and the second image to generate a final target encrypted image which simultaneously has anti-noise disturbance and auxiliary noise disturbance. The final target encrypted image can prevent some malicious programs or other people from stealing the privacy information on the user terminal by using an artificial intelligence algorithm, and the cost of obtaining the privacy information by a malicious source is increased.
It can be understood that the auxiliary noise is moire noise, that is, only moire noise is added to the target region, and the target region of the obtained target encrypted image has a "shielding" effect of moire noise structure. The auxiliary noise is random noise, that is, random noise is only added to the target area, and the target area of the obtained target encrypted image has a shielding effect of a random noise structure. The auxiliary noise is moire noise and random noise, that is, the target area has moire noise and random noise at the same time, and the target area of the obtained target encrypted image can present a shielding effect of a superposition structure of the random noise and the moire noise.
In an embodiment of the present application, in a case where the auxiliary noise image includes a random noise image and a moire noise image, fig. 3 shows a fourth flowchart of an image encryption method of an embodiment of the present application, including:
wherein the priority is related to the privacy level of the content to be encrypted. The information in the content to be encrypted can be determined by the recognition model, and then the corresponding priority is determined by the information. Or the priority of the content to be encrypted is specified by the user.
in this embodiment, considering that the information contained in the content to be encrypted that needs to be encrypted has different degrees of privacy, some information may expose the personal information of the user, such as an identification number, a bank password, and the like, and needs a strong encryption effect; some information has low privacy degree, such as a positioning map, a company name and the like, and although the information belongs to the information related to the user, the information cannot cause adverse effect on the user even if the information is leaked in some scenes. Therefore, the target area is divided into the first area and the second area according to the priority of the content to be encrypted, the positions of the first area and the second area in the original image are respectively marked through the first mask and the second mask, and in the image encryption process, different shielding effects are added to the content to be encrypted with different privacy degrees, so that the visual effect and the safety of the target encrypted image are considered, and the use experience of a user is improved.
Specifically, for example, the original image includes text, graphics and blank, and the text and graphics are contents to be encrypted that need to be encrypted. The method includes recognizing the position of the character content in the original image, dividing the original image, determining a character region (first region), and generating masks (first mask and second mask) representing the position of the character region (first region) and the position of a non-character region (second region). For example, the matrix element value of the position where the text region is located is 1, the position of the text region is not detected, and the matrix element values are all zero.
and 310, performing superposition operation on the first sub-image and the second sub-image according to a second preset weight to generate a second image.
The second preset weight is used for indicating the proportion of the first sub-image to the second sub-image during the superposition operation, and further controlling the encryption intensity of random noise and moire noise in the second image.
In this embodiment, the element correspondence product operation is performed on one of the random noise image and the moire noise image and the first mask, so that the resulting first region of the first sub-image retains the random noise or the moire noise. Likewise, the element-wise product operation is performed on the random noise image and the other of the moire noise image and the second mask such that the second region of the generated second sub-image retains the other of the random noise or the moire noise. And according to a second preset weight, performing signal-noise fusion processing on the first sub-image and the second sub-image to obtain a second image. Thereby add random noise and mole line noise respectively for first region and second region in the second image, make the content of treating encryption of different privacy degree have different "shelters from" effect, the visual effect of target encryption image has not only been guaranteed, and, encrypt original image through the noise of multiple difference, can effectively strengthen some malicious programs or other people and utilize artificial intelligence algorithm to break the complexity of target encryption image, improve the cost that malicious source obtained privacy information, and then compromise visual effect and security, promote user's use and experience.
Specifically, for example, as shown in fig. 8, the mask at the position of the text region (first region) is 1, and the masks at the positions where the text region (second region) is not detected are all zeros. The random noise matrix and the text area mask carry out element corresponding product operation, so that the first sub-image only keeps the random noise of the text area, and the non-text area is a matrix with all zero pixel values, namely the random noise is not added in the first sub-image. Performing element corresponding product operation on the Moire patterns and the non-character area mask, wherein the Moire patterns are reserved in the non-character area of the first subimage, and the character area has no Moire patterns; if the entire image is text, the entire image is a matrix with all zero pixel values, and then moire noise is not added to the second sub-image.
In an embodiment of the present application, as shown in fig. 4, step 302, dividing the target area into a first area and a second area according to the priority of the content to be encrypted, includes:
wherein the setting interface includes all types of content that may appear in the image, such as text, graphics, symbols, charts, and the like.
wherein the first input includes, but is not limited to, a click input, a key input, a fingerprint input, a swipe input, and a press input. The key input includes, but is not limited to, a power key, a volume key, a single-click input of a main menu key, a double-click input, a long-press input, a combination key input, etc. to the electronic device. Of course, the first input may also be other operations of the electronic device by the user, and the operation manner in the embodiment of the present application is not particularly limited, and may be any realizable manner.
in this embodiment, in the setting interface of the system setting, different priorities can be configured for the contents to be encrypted through the first input, that is, the privacy degree of different types of contents possibly existing in the image can be set by the user. Specifically, the priority is set for the content which may appear in the image through the first input, and when the content to be encrypted in the image needs to be encrypted, only the priority corresponding to the type of the content to be encrypted needs to be searched.
Specifically, for example, 2 possible content types, namely "text" and "graphic" are displayed on the setting interface. The user clicks the 'text', a setting window is displayed near the 'text', and the priority of the preset content type of the 'text' input by the user in the setting window is 3. In the process of the original image, when the content to be encrypted is identified as characters, the priority of the content to be encrypted is determined to be 3.
and step 410, taking the region except the first region in the target region as a second region.
In this embodiment, a preset priority is used as a basis for classifying the target content, an area where the content to be encrypted whose priority is higher than the preset priority is located is used as a first area, an area other than the first area in the target area is used as a second area, and the second area is an area where the content to be encrypted whose priority is lower than or equal to the preset priority is located. Therefore, the target area is divided, different shielding effects are added for the contents to be encrypted with different privacy degrees, the visual effect and the safety of the target encrypted image are considered, and the use experience of a user is improved.
In one embodiment of the present application, as shown in fig. 5, step 106, adding a counternoise to the original image, generating a noisy image, comprises:
the preset anti-noise template is generated based on a preset sample image and a Universal Additive Perturbation (UAP) algorithm.
And step 504, performing superposition operation on the original image and a preset anti-noise template to generate an anti-noise image.
In this embodiment, since the UAP algorithm takes a long time to solve the optimal disturbance in an iterative manner and has a high system computation capability, classification algorithm models on a server or other electronic devices, such as a VGG model, a ResNet model, and a MobileNetV3 model, are utilized in advance. And performing multiple rounds of iterative computation on the classification task of the preset sample image to obtain a preset pair anti-noise template which enables the error recognition rate of the classification algorithm to reach 85%. In the process of encrypting the original image, the preset anti-noise template corresponding to the original image is directly utilized to add anti-noise for the original image. Therefore, the requirement of the electronic equipment for encryption processing on the computing capacity is reduced, the time for solving the optimal disturbance is saved, and the image encryption efficiency is improved.
In one embodiment of the present application, as shown in fig. 6, the auxiliary noise includes moir e noise, and step 106, adding the auxiliary noise to the original image, and generating a noise image includes:
and 606, performing superposition operation on the first moire noise image and the second moire noise image to generate a moire noise image.
In this embodiment, the original image is input into a preset moire model to add moire noise to the original image through the preset moire model, resulting in a first moire noise image having moire noise associated with the preset moire model. Further, the moire noise in the first moire noise image is modified according to a preset offset parameter, and a second moire noise image with different moire noise from the first moire noise image is obtained. Through mole line noise in the first mole line noise image of stack and the second mole line noise image for the mole line noise image that finally generates demonstrates the mole line of multiple orientation or size, is favorable to strengthening the interference of mole line noise to the target content, promotes the encryption effect of original image, and then can effectively strengthen the interference that utilizes artificial intelligence algorithm to some malicious program or other people, and protection user's privacy is not revealed.
The preset offset parameter can be reasonably set according to the encryption intensity of the moire noise by the user, and comprises an offset direction and an offset. It is understood that when the offset amount is 0, that is, the moire noise is not offset-processed, the second moire noise image is the same as the first moire noise image.
Specifically, for example, a set of preset moire models capable of generating moire noise on an image is trained by using an artificial intelligence algorithm UNet and a photographed image with moire as training data. After the original image is input to the preset moire model, the preset moire model outputs a first moire noise image with a single moire noise, and the moire noise is rotated clockwise by 180 degrees (preset offset parameter) based on the first moire noise image to form a new second moire noise image. And superposing the second moire noise image with the first moire noise image output by the model to obtain a moire noise image with two moire circles, namely a bidirectional moire noise image. Of course, it is also possible to rotate this moir e noise clockwise 2 times by 90 ° based on the first moir e noise image, resulting in two second moir e noise images rotated by 90 ° and 180 °, and when the two second moir pattern noise images are superimposed with the first moir pattern noise image, a three-way moir pattern noise image is formed.
In one embodiment of the present application, as shown in fig. 7, the auxiliary noise includes random noise, and step 106, adding the auxiliary noise to the original image, and generating a noise image includes:
the frequency domain transformation operation includes fourier transformation, discrete cosine transformation, wavelet transformation, and the like.
In this embodiment, the original image is transformed to the frequency domain (wavelet domain) using a frequency domain transform operation, and frequency domain information of the original image is determined. And randomly generating random noise matched with the frequency domain information, and updating the frequency domain information according to the random noise so as to add the random noise to the original image in the frequency domain. And performing inverse transformation operation on the original image after the frequency domain information is updated, and transforming the image into a space domain (a space domain of the image) through inverse transformation to obtain a random noise image with random noise. Compared with a mode of adding random noise based on an image space domain, the mode of adding random noise through a frequency domain has stronger hiding performance and higher attack resistance, can effectively strengthen the interference of some malicious programs or other people by using an artificial intelligence algorithm, and protects the privacy of a user from being revealed.
In one embodiment of the present application, as shown in fig. 9, an image encryption apparatus 900 includes: the determining module 902, the determining module 902 is configured to determine a target area where content to be encrypted in an original image to be encrypted is located; the mask module 904, the mask module 904 is used for performing mask processing on the target area, and determining mask information of the target area; a noise adding module 906, wherein the noise adding module 906 is used for adding the counternoise and the auxiliary noise on the original image to generate a noise image; and the generating module 908 is configured to perform fusion processing on the original image, the noise image, and the mask information to generate a target encrypted image.
In the embodiment, the anti-noise and auxiliary noise contained in the target encrypted image can be utilized to interfere with the image information on which the image identification algorithm depends, so that the image identification fails, the encryption of the image is realized, the encryption effect is ensured, meanwhile, different keys do not need to be set for different images, the requirements on the calculation and storage of the system are greatly reduced, and the safety and efficiency of the image encryption are improved.
Optionally, the noise image includes a contrast noise image and an auxiliary noise image; a generating module 908, configured to perform a superposition operation on the original image and the anti-noise image to generate a first image; performing element corresponding product operation on the auxiliary noise image and the mask information to generate a second image; and according to the first preset weight, performing superposition operation on the first image and the second image to generate a target encrypted image.
Optionally, in a case where the auxiliary noise image includes a random noise image and a moire noise image, the image encryption apparatus 900 further includes: a dividing module (not shown in the figure) for dividing the target area into a first area and a second area according to the priority of the content to be encrypted; the mask module 904 is further configured to perform mask processing on the first area and the second area, respectively, and determine a first mask of the first area and a second mask of the second area; a generating module 908, further configured to perform element-wise product operation on one of the random noise image and the moire noise image and the first mask to generate a first sub-image; performing element corresponding product operation on the other of the random noise image and the moire noise image and the second mask to generate a second sub-image; and performing superposition operation on the first sub-image and the second sub-image according to a second preset weight to generate a second image.
Optionally, the image encryption apparatus 900 further includes: a display module (not shown in the figure) for displaying the setting interface; a receiving module (not shown in the figure) for receiving a first input to the setting interface; a setting module (not shown in the figure) for setting a priority of the content to be encrypted in response to a first input; the segmentation module is also used for taking the area where the content to be encrypted with the priority higher than the preset priority is located as a first area; and taking the region except the first region in the target region as a second region.
Optionally, the image encryption apparatus 900 further includes: a first obtaining module (not shown in the figure), configured to obtain a preset pair of anti-noise templates corresponding to an original image, where the preset pair of anti-noise templates are generated based on a preset sample image and a universal antagonistic disturbance algorithm; the noise adding module 906 is further configured to perform a superposition operation on the original image and a preset pair of anti-noise templates to generate an anti-noise image.
Optionally, the noise adding module 906 is further configured to input the original image into a preset moire model, and generate a first moire noise image; processing Moire noise in the first Moire noise image according to a preset offset parameter to generate a second Moire noise image; and performing superposition operation on the first moire noise image and the second moire noise image to generate a moire noise image.
Optionally, the noise adding module 906 is further configured to perform frequency domain transformation operation on the original image to determine frequency domain information of the original image; the image encryption apparatus 900 further includes: a second obtaining module (not shown in the figure), configured to obtain random noise corresponding to the frequency domain information; a noise adding module 906, further configured to update the frequency domain information according to the random noise; and performing inverse transformation operation on the original image after the frequency domain information is updated to generate a random noise image.
In this embodiment, when each module of the image encryption apparatus 900 executes its respective function, the steps of the image encryption method in any embodiment of the first aspect are implemented, and therefore, the image encryption apparatus 900 also includes all the beneficial effects of the image encryption method in any embodiment of the first aspect, which are not described herein again.
The image encryption device in the embodiment of the present application may be a device, or may be a component, an integrated circuit, or a chip in a terminal. The device is a mobile electronic device and is also a non-mobile electronic device. The mobile electronic device is illustratively a mobile phone, a tablet computer, a notebook computer, a palm top computer, a vehicle-mounted electronic device, an intelligent camera device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a Personal Digital Assistant (PDA), and the like, and the non-mobile electronic device is a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a self-service machine, and the like, and the embodiment of the present application is not particularly limited.
The management device of the application program in the embodiment of the present application is a device having an operating system. The operating system is an Android operating system, an iOS operating system, and other operating systems, and the embodiments of the present application are not limited specifically.
In one embodiment of the present application, as shown in fig. 10, there is provided an electronic device 1000 comprising: the processor 1004, the memory 1002, and the program or the instructions stored in the memory 1002 and executed on the processor 1004, where the program or the instructions are executed by the processor 1004 to implement the steps of the image encryption method provided in any of the above embodiments, and therefore, the electronic device 1000 includes all the advantages of the image encryption method provided in any of the above embodiments, which are not described herein again.
It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic device and the non-mobile electronic device described above.
Fig. 11 is a schematic hardware configuration diagram of an electronic device 1100 implementing an embodiment of the present application. The electronic device 1100 includes, but is not limited to: a radio frequency unit 1101, a network module 1102, an audio output unit 1103, an input unit 1104, a sensor 1105, a display unit 1106, a user input unit 1107, an interface unit 1108, a memory 1109, a processor 1110, and the like.
Those skilled in the art will appreciate that the electronic device 1100 may further include a power source (e.g., a battery) for supplying power to the various components, and the power source may be logically connected to the processor 1110 via a power management system, so as to manage charging, discharging, and power consumption management functions via the power management system. The electronic device structure shown in fig. 11 does not constitute a limitation of the electronic device, and the electronic device may include more or less components than those shown, or combine some components, or arrange different components, and thus, the description is not repeated here.
The processor 1110 is configured to determine a target area where content to be encrypted in an original image to be encrypted is located; performing mask processing on the target area, and determining mask information of the target area; adding counternoise and auxiliary noise on the original image to generate a noise image; and fusing the original image, the noise image and the mask information to generate a target encrypted image.
In the embodiment, the anti-noise and auxiliary noise contained in the target encrypted image can be utilized to interfere with the image information on which the image identification algorithm depends, so that the image identification fails, the encryption of the image is realized, the encryption effect is ensured, meanwhile, different keys do not need to be set for different images, the requirements on the calculation and storage of the system are greatly reduced, and the safety and efficiency of the image encryption are improved.
Further, the noise image includes a contrast noise image and an auxiliary noise image; the processor 1110 is further configured to perform a superposition operation on the original image and the anti-noise image to generate a first image; performing element corresponding product operation on the auxiliary noise image and the mask information to generate a second image; and according to the first preset weight, performing superposition operation on the first image and the second image to generate a target encrypted image.
Further, in the case where the auxiliary noise image includes a random noise image and a moire noise image, the processor 1110 is further configured to divide the target area into a first area and a second area according to the priority of the content to be encrypted; respectively performing mask processing on the first area and the second area, and determining a first mask of the first area and a second mask of the second area; performing element corresponding product operation on one of the random noise image and the moire noise image and the first mask to generate a first sub-image; performing element corresponding product operation on the other of the random noise image and the moire noise image and the second mask to generate a second sub-image; and performing superposition operation on the first sub-image and the second sub-image according to a second preset weight to generate a second image.
Further, the display unit 1106 is used to display a setting interface; the user input unit 1107 is used to receive a first input to the setting interface; processor 1110 is further configured to set a priority of content to be encrypted in response to the first input; taking the area where the content to be encrypted with the priority higher than the preset priority as a first area; and taking the region except the first region in the target region as a second region.
Further, the processor 1110 is further configured to obtain a preset anti-noise template corresponding to the original image, where the preset anti-noise template is generated based on a preset sample image and a universal anti-noise perturbation algorithm; and carrying out superposition operation on the original image and a preset anti-noise template to generate an anti-noise image.
Further, the processor 1110 is further configured to input the original image into a preset moire model, and generate a first moire noise image; processing Moire noise in the first Moire noise image according to a preset offset parameter to generate a second Moire noise image; and performing superposition operation on the first moire noise image and the second moire noise image to generate a moire noise image.
Further, the processor 1110 is further configured to perform a frequency domain transform operation on the original image, and determine frequency domain information of the original image; acquiring random noise corresponding to frequency domain information; updating frequency domain information according to random noise; and performing inverse transformation operation on the original image after the frequency domain information is updated to generate a random noise image.
It should be understood that in the embodiment of the present application, the input Unit 1104 may include a Graphics Processing Unit (GPU) 1141 and a microphone 1142, and the Graphics Processing Unit 1141 processes image data of a still picture or a video obtained by an image capturing device (such as a camera) in a video capturing mode or an image capturing mode. The display unit 1106 may include a display panel 1161, and the display panel 1161 may be configured in the form of a liquid crystal display, an organic light emitting diode, or the like. The user input unit 1107 includes a touch panel 1171 and other input devices 1172. Touch panel 1171, also referred to as a touch screen. Touch panel 1171 can include two portions, a touch detection device and a touch controller. Other input devices 1172 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein. The memory 1109 may be used for storing software programs and various data including, but not limited to, application programs and an operating system. Processor 1110 may integrate an application processor that handles primarily operating systems, user interfaces, applications, etc. and a modem processor that handles primarily wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 1110.
In one embodiment of the present application, there is provided a read storage medium having stored thereon a program or instructions which, when executed by a processor, implement the steps of the image encryption method provided in any one of the above embodiments.
In this embodiment, reading the storage medium can implement each process of the image encryption method provided in the embodiment of the present application, and can achieve the same technical effect, and for avoiding repetition, details are not described here again.
The processor is the processor in the communication device in the above embodiment. The Read-storage medium includes a computer-readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
The embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to execute a program or an instruction to implement each process of the above-mentioned embodiment of the image encryption method, and can achieve the same technical effect, and in order to avoid repetition, the description is omitted here.
It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.
It should be noted that, in this document, 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. Further, it should be noted that the scope of the methods and apparatus of the embodiments of the present application is not limited to performing the functions in the order illustrated or discussed, but may include performing the functions in a substantially simultaneous manner or in a reverse order based on the functions involved, e.g., the methods described may be performed in an order different than that described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (14)
1. An image encryption method, comprising:
determining a target area where to-be-encrypted content in an original image to be encrypted is located;
performing mask processing on the target area, and determining mask information of the target area;
adding counternoise and auxiliary noise on the original image to generate a noise image;
and fusing the original image, the noise image and the mask information to generate a target encrypted image.
2. The image encryption method according to claim 1, wherein the noise image includes a countermeasure noise image and an auxiliary noise image; the fusing the original image, the noise image and the mask information to generate the target encrypted image includes:
performing superposition operation on the original image and the anti-noise image to generate a first image;
performing element-corresponding product operation on the auxiliary noise image and the mask information to generate a second image;
and according to a first preset weight, performing superposition operation on the first image and the second image to generate the target encrypted image.
3. The image encryption method according to claim 2,
the mask processing on the target area and determining mask information of the target area include:
dividing the target area into a first area and a second area according to the priority of the content to be encrypted;
respectively performing mask processing on the first area and the second area, and determining a first mask of the first area and a second mask of the second area;
the auxiliary noise image comprises a random noise image and a moire noise image; performing element-wise product operation on the auxiliary noise image and the mask information to generate a second image, including:
performing element-corresponding product operation on one of the random noise image and the moire noise image and the first mask to generate a first sub-image;
performing element-corresponding product operation on the other of the random noise image and the moire noise image and the second mask to generate a second sub-image;
and performing superposition operation on the first sub-image and the second sub-image according to a second preset weight to generate the second image.
4. The image encryption method according to any one of claims 1 to 3, wherein the adding of the countermeasure noise to the original image to generate a noise image includes:
acquiring a preset anti-noise template corresponding to the original image, wherein the preset anti-noise template is generated on the basis of a preset sample image and a universal antagonistic disturbance algorithm;
and performing superposition operation on the original image and the preset pair of anti-noise templates to generate an anti-noise image.
5. The image encryption method according to any one of claims 1 to 3, wherein the auxiliary noise includes moir e noise, and the adding auxiliary noise to the original image to generate a noise image includes:
inputting the original image into a preset moire pattern model to generate a first moire pattern noise image;
processing Moire noise in the first Moire noise image according to a preset offset parameter to generate a second Moire noise image;
and performing superposition operation on the first moire noise image and the second moire noise image to generate a moire noise image.
6. The image encryption method according to any one of claims 1 to 3, wherein the auxiliary noise includes random noise, and the adding auxiliary noise to the original image to generate a noise image includes:
performing frequency domain transformation operation on the original image to determine frequency domain information of the original image;
acquiring random noise corresponding to the frequency domain information;
updating the frequency domain information according to the random noise;
and performing inverse transformation operation on the original image after the frequency domain information is updated to generate a random noise image.
7. An image encryption apparatus characterized by comprising:
the determining module is used for determining a target area where the content to be encrypted in the original image to be encrypted is located;
the mask module is used for performing mask processing on the target area and determining mask information of the target area;
the noise adding module is used for adding counternoise and auxiliary noise on the original image to generate a noise image;
and the generating module is used for carrying out fusion processing on the original image, the noise image and the mask information to generate a target encrypted image.
8. The image encryption apparatus according to claim 7, wherein the noise image includes a countermeasure noise image and an auxiliary noise image;
the generating module is further configured to perform a superposition operation on the original image and the anti-noise image to generate a first image;
performing element-corresponding product operation on the auxiliary noise image and the mask information to generate a second image;
and according to a first preset weight, performing superposition operation on the first image and the second image to generate the target encrypted image.
9. The image encryption apparatus according to claim 8, wherein the auxiliary noise image includes a random noise image and a moir e noise image, the image encryption apparatus further comprising:
the segmentation module is used for dividing the target area into a first area and a second area according to the priority of the content to be encrypted;
the mask module is further configured to perform mask processing on the first area and the second area, respectively, and determine a first mask of the first area and a second mask of the second area;
the generating module is further configured to perform element-corresponding product operation on one of the random noise image and the moire noise image and the first mask to generate a first sub-image;
performing element-corresponding product operation on the other of the random noise image and the moire noise image and the second mask to generate a second sub-image;
and performing superposition operation on the first sub-image and the second sub-image according to a second preset weight to generate the second image.
10. The image encryption device according to any one of claims 7 to 9, characterized by further comprising:
the first acquisition module is used for acquiring a preset anti-noise template corresponding to the original image, and the preset anti-noise template is generated based on a preset sample image and a universal anti-noise disturbance algorithm;
the noise adding module is further configured to perform superposition operation on the original image and the preset pair of anti-noise templates to generate an anti-noise image.
11. The image encryption apparatus according to any one of claims 7 to 9,
the noise adding module is further used for inputting the original image into a preset moire pattern model to generate a first moire pattern noise image;
processing Moire noise in the first Moire noise image according to a preset offset parameter to generate a second Moire noise image;
and performing superposition operation on the first moire noise image and the second moire noise image to generate a moire noise image.
12. The image encryption apparatus according to any one of claims 7 to 9,
the noise adding module is further configured to perform frequency domain transformation operation on the original image to determine frequency domain information of the original image;
the image encryption apparatus further includes:
the second acquisition module is used for acquiring random noise corresponding to the frequency domain information;
the noise adding module is further configured to update the frequency domain information according to the random noise;
and performing inverse transformation operation on the original image after the frequency domain information is updated to generate a random noise image.
13. An electronic device comprising a processor, a memory and a program or instructions stored on the memory and executable on the processor, the program or instructions, when executed by the processor, implementing the steps of the image encryption method according to any one of claims 1 to 6.
14. A readable storage medium, characterized in that it stores thereon a program or instructions which, when executed by a processor, implement the steps of the image encryption method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110830378.4A CN113486377A (en) | 2021-07-22 | 2021-07-22 | Image encryption method and device, electronic equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110830378.4A CN113486377A (en) | 2021-07-22 | 2021-07-22 | Image encryption method and device, electronic equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113486377A true CN113486377A (en) | 2021-10-08 |
Family
ID=77942995
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110830378.4A Pending CN113486377A (en) | 2021-07-22 | 2021-07-22 | Image encryption method and device, electronic equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113486377A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114331797A (en) * | 2021-12-30 | 2022-04-12 | 北京百度网讯科技有限公司 | Image data encryption method, image data decryption device and electronic equipment |
| CN115049760A (en) * | 2022-08-16 | 2022-09-13 | 杭州海康威视数字技术股份有限公司 | Moore effect enhancement-based video privacy protection method, device and equipment |
| WO2023065637A1 (en) * | 2021-10-22 | 2023-04-27 | 平安科技（深圳）有限公司 | Data processing method and apparatus, and electronic device and storage medium |
| CN117132477A (en) * | 2023-02-24 | 2023-11-28 | 荣耀终端有限公司 | Image processing method and electronic equipment |
| CN117611422A (en) * | 2024-01-23 | 2024-02-27 | 暨南大学 | Image steganography method based on Moire pattern generation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108989678A (en) * | 2018-07-27 | 2018-12-11 | 维沃移动通信有限公司 | A kind of image processing method, mobile terminal |
| CN109993824A (en) * | 2017-12-29 | 2019-07-09 | 深圳市优必选科技有限公司 | Image processing method, intelligent terminal and the device with store function |
| CN110599410A (en) * | 2019-08-07 | 2019-12-20 | 北京达佳互联信息技术有限公司 | Image processing method, device, terminal and storage medium |
| CN111768325A (en) * | 2020-04-03 | 2020-10-13 | 南京信息工程大学 | Security improvement method based on generation of countermeasure sample in big data privacy protection |
| CN112001983A (en) * | 2020-10-30 | 2020-11-27 | 深圳佑驾创新科技有限公司 | Method and device for generating occlusion image, computer equipment and storage medium |
| CN112040086A (en) * | 2019-06-03 | 2020-12-04 | 湖北微模式科技发展有限公司 | Image encryption and decryption method and device, equipment and readable storage medium |
| CN112132106A (en) * | 2020-10-09 | 2020-12-25 | 腾讯科技（北京）有限公司 | Image augmentation processing method, device and equipment based on artificial intelligence and storage medium |
-
2021
- 2021-07-22 CN CN202110830378.4A patent/CN113486377A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109993824A (en) * | 2017-12-29 | 2019-07-09 | 深圳市优必选科技有限公司 | Image processing method, intelligent terminal and the device with store function |
| CN108989678A (en) * | 2018-07-27 | 2018-12-11 | 维沃移动通信有限公司 | A kind of image processing method, mobile terminal |
| CN112040086A (en) * | 2019-06-03 | 2020-12-04 | 湖北微模式科技发展有限公司 | Image encryption and decryption method and device, equipment and readable storage medium |
| CN110599410A (en) * | 2019-08-07 | 2019-12-20 | 北京达佳互联信息技术有限公司 | Image processing method, device, terminal and storage medium |
| CN111768325A (en) * | 2020-04-03 | 2020-10-13 | 南京信息工程大学 | Security improvement method based on generation of countermeasure sample in big data privacy protection |
| CN112132106A (en) * | 2020-10-09 | 2020-12-25 | 腾讯科技（北京）有限公司 | Image augmentation processing method, device and equipment based on artificial intelligence and storage medium |
| CN112001983A (en) * | 2020-10-30 | 2020-11-27 | 深圳佑驾创新科技有限公司 | Method and device for generating occlusion image, computer equipment and storage medium |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023065637A1 (en) * | 2021-10-22 | 2023-04-27 | 平安科技（深圳）有限公司 | Data processing method and apparatus, and electronic device and storage medium |
| CN114331797A (en) * | 2021-12-30 | 2022-04-12 | 北京百度网讯科技有限公司 | Image data encryption method, image data decryption device and electronic equipment |
| CN115049760A (en) * | 2022-08-16 | 2022-09-13 | 杭州海康威视数字技术股份有限公司 | Moore effect enhancement-based video privacy protection method, device and equipment |
| CN115049760B (en) * | 2022-08-16 | 2022-12-02 | 杭州海康威视数字技术股份有限公司 | Moore effect enhancement-based video privacy protection method, device and equipment |
| CN117132477A (en) * | 2023-02-24 | 2023-11-28 | 荣耀终端有限公司 | Image processing method and electronic equipment |
| CN117611422A (en) * | 2024-01-23 | 2024-02-27 | 暨南大学 | Image steganography method based on Moire pattern generation |
| CN117611422B (en) * | 2024-01-23 | 2024-05-07 | 暨南大学 | Image steganography method based on Moire pattern generation |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113486377A (en) | Image encryption method and device, electronic equipment and readable storage medium | |
| US20200218794A1 (en) | Identity authentication, unlocking, and payment methods and apparatuses, storage media, products, and devices | |
| CN111461089A (en) | Face detection method, and training method and device of face detection model | |
| CN112804445B (en) | Display method and device and electronic equipment | |
| US20230045306A1 (en) | Face liveness detection method, system, apparatus, computer device, and storage medium | |
| CN105320871A (en) | Screen unlocking method and screen unlocking apparatus | |
| CN104573456A (en) | Terminal interface control method | |
| US20230089622A1 (en) | Data access control for augmented reality devices | |
| CN110619239A (en) | Application interface processing method and device, storage medium and terminal | |
| CN112581344A (en) | Image processing method and device, computer equipment and storage medium | |
| Sarmah et al. | Optimization models in steganography using metaheuristics | |
| CN116168038A (en) | Image reproduction detection method and device, electronic equipment and storage medium | |
| Bilgi et al. | A shoulder-surfing resistant graphical authentication method | |
| CN109669537B (en) | A kind of man-machine interactive system based on computer virtual interface | |
| US20240152631A1 (en) | Data access control for user devices using a blockchain | |
| Prabhu | Image based authentication using illusion pin for shoulder surfing attack | |
| CN112163209B (en) | Application management method and device and electronic equipment | |
| CN116361761A (en) | Information shielding method, information shielding device and electronic equipment | |
| CN112883951A (en) | Method, system and storage medium for protecting sensitive content | |
| CN112765620A (en) | Display control method, display control device, electronic device, and medium | |
| CN106779522B (en) | Article control mark setting and article identification method and device | |
| Gayathri et al. | Secure authentication mechanism for users using virtual reality | |
| CN115134473B (en) | Image encryption method and device | |
| CN112560753B (en) | Face recognition method, device, equipment and storage medium based on feature fusion | |
| CN113282899B (en) | Object management method, device, electronic equipment and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |