WO2021217899A1 - Procédé, appareil et dispositif de chiffrement d'informations d'affichage et support de stockage - Google Patents

Procédé, appareil et dispositif de chiffrement d'informations d'affichage et support de stockage Download PDF

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Publication number
WO2021217899A1
WO2021217899A1 PCT/CN2020/102535 CN2020102535W WO2021217899A1 WO 2021217899 A1 WO2021217899 A1 WO 2021217899A1 CN 2020102535 W CN2020102535 W CN 2020102535W WO 2021217899 A1 WO2021217899 A1 WO 2021217899A1
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WIPO (PCT)
Prior art keywords
display area
image
target
information
current
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PCT/CN2020/102535
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English (en)
Chinese (zh)
Inventor
温桂龙
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深圳壹账通智能科技有限公司
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Publication of WO2021217899A1 publication Critical patent/WO2021217899A1/fr

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    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2107—File encryption

Definitions

  • This application relates to the field of information security technology, and in particular to an encryption method, device, device, and computer-readable storage medium for displaying information.
  • the main purpose of this application is to provide an encryption method, device, device, and computer-readable storage medium for displaying information, aiming to solve the technical problem of poor anti-leakage effects of existing devices on displaying information.
  • the encryption method for display information includes the following steps:
  • the target sensitivity level of the currently displayed information is acquired, and when the target sensitivity level reaches the preset sensitivity level, the display of the target display area corresponding to the current device is collected according to the first preset frequency The first image of the area;
  • the present application also provides an encryption device for displaying information, and the encryption device for displaying information includes:
  • the first image acquisition module is used to acquire the target sensitivity level of the currently displayed information when the current device display information is monitored, and when the target sensitivity level reaches the preset sensitivity level, collect the current The first image of the display area of the target display area corresponding to the device;
  • An area device monitoring module configured to determine whether there is a camera device in the target display area according to a preset camera device recognition model and the first image of the display area;
  • the display information encryption module is configured to perform corresponding encryption processing on the current device and/or current display information when there is a camera device in the target display area.
  • the present application also provides an encryption device for displaying information.
  • the encryption device for displaying information includes a processor, a memory, and display information that is stored on the memory and can be executed by the processor.
  • the encryption program of the display information when the encryption program of the display information is executed by the processor, the following steps are implemented:
  • the target sensitivity level of the currently displayed information is acquired, and when the target sensitivity level reaches the preset sensitivity level, the display of the target display area corresponding to the current device is collected according to the first preset frequency The first image of the area;
  • the present application also provides a computer-readable storage medium that stores an encryption program for displaying information, where the encryption program for displaying information is executed by a processor. The following steps:
  • the target sensitivity level of the currently displayed information is acquired, and when the target sensitivity level reaches the preset sensitivity level, the display of the target display area corresponding to the current device is collected according to the first preset frequency The first image of the area;
  • the present application provides an encryption method for display information, by acquiring the target sensitivity level of the currently displayed information when the current device display information is monitored, and when the target sensitivity level reaches the preset sensitivity level, according to the first preset frequency Collect the first image of the display area of the target display area corresponding to the current device; determine whether there is a camera in the target display area according to a preset camera device recognition model and the first image of the display area; display on the target When there is a camera device in the area, corresponding encryption processing is performed on the current device and/or the current display information.
  • the present application recognizes the display area image corresponding to the current device through the camera device recognition model, that is, the display area image is classified through the KNN algorithm and the preset image type for real-time detection Whether there is a camera device that causes display information leakage in the display area of the current device.
  • FIG. 1 is a schematic diagram of the hardware structure of an encryption device for displaying information involved in a solution of an embodiment of the application;
  • FIG. 2 is a schematic flowchart of a first embodiment of a method for encrypting display information in this application
  • FIG. 3 is a schematic flowchart of a second embodiment of a method for encrypting display information in this application
  • FIG. 4 is a schematic flowchart of a third embodiment of a method for encrypting display information in this application.
  • FIG. 5 is a schematic diagram of the functional modules of the first embodiment of the encryption device for displaying information in this application.
  • the encryption method for display information involved in the embodiments of the present application is mainly applied to an encryption device for displaying information.
  • the encryption device for displaying information may be a device with display and processing functions such as a PC, a portable computer, and a mobile terminal.
  • FIG. 1 is a schematic diagram of the hardware structure of the encryption device for displaying information involved in the solution of the embodiment of the application.
  • the encryption device for displaying information may include a processor 1001 (for example, a CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005.
  • the communication bus 1002 is used to realize the connection and communication between these components;
  • the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard);
  • the network interface 1004 may optionally include a standard wired interface, a wireless interface (Such as WI-FI interface);
  • the memory 1005 can be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory.
  • the memory 1005 can optionally also be a storage device independent of the aforementioned processor 1001 .
  • FIG. 1 does not constitute a limitation on the encryption device for displaying information, and may include more or less components than those shown in the figure, or a combination of certain components, or different components. Layout.
  • the memory 1005 as a computer-readable storage medium in FIG. 1 may include an operating system, a network communication module, and an encrypted program for displaying information.
  • the network communication module is mainly used to connect to the server and perform data communication with the server; and the processor 1001 can call the encryption program of the display information stored in the memory 1005, and execute the encryption method of the display information provided by the embodiment of the present application .
  • the embodiment of the present application provides an encryption method for display information.
  • FIG. 2 is a schematic flowchart of a first embodiment of a method for encrypting display information in this application.
  • the encryption method of the displayed information includes the following steps:
  • Step S10 When the current device display information is monitored, the target sensitivity level of the currently displayed information is acquired, and when the target sensitivity level reaches a preset sensitivity level, the target display corresponding to the current device is collected according to the first preset frequency The first image of the display area of the area;
  • Information security is an important topic in the modern Internet. Whether it is in a specific government agency or various computer systems in various enterprises, there will be some specific information in the system that is relatively confidential information, and should not be It is transmitted to the external Internet environment.
  • the general method will prevent the leakage of sensitive information through various forms such as isolation of internal and external networks, restriction of USB and other forms of data transmission to the outside.
  • this application uses the camera device recognition model to identify the display area image corresponding to the current device when the device displays the display information of the target sensitivity level. Detect whether there is a camera device that causes display information leakage in the display area of the current device.
  • the currently displayed information includes text information, picture information, or video information.
  • text information is taken as an example for description.
  • the preset sensitivity level can be preset to "non-sensitive level", “general sensitivity level”, and "high sensitivity level”.
  • the terminal can detect the sensitivity level of the current text content in real time or regularly.
  • multiple text content containing non-sensitive, general sensitive, and high sensitivity can be obtained, and multiple text content containing non-sensitive, generally sensitive, and highly sensitive can be used as the training set, and the training set can be input to the volume.
  • the product neural network is trained to build a sensitivity level recognition model, and the sensitivity level of the current text content is detected through the sensitivity level recognition model.
  • the first image of the display area of the target display area corresponding to the current device is collected through the front camera of the terminal at the first preset frequency.
  • the first preset frequency is set according to the user's own needs.
  • step S10 specifically includes:
  • the currently displayed information is text information
  • extract keywords in the currently displayed information and determine the target sensitivity level of the currently displayed information according to the keywords
  • the target sensitivity level reaches the preset sensitivity level
  • the first image of the display area of the target display area corresponding to the current device is acquired according to the first preset frequency.
  • the terminal when the terminal detects the current text information, it extracts the keywords of the current text information and determines whether the keywords are preset storage keywords. If the keywords are preset storage keywords, the current text information is determined according to the keywords. Sensitivity level. If it is detected that the sensitivity level of the current text information belongs to the non-sensitive level in the preset sensitivity level, no operation is performed on the current text, that is, the current text content does not need to be protected; if the sensitivity level of the current text information is detected as normal When the sensitivity level is sensitive, the face information of the current user is obtained through the front camera of the terminal to detect whether the face information of the current user matches the face information of the preset storage user.
  • the current user is not the preset storage user, then Add a watermark containing the preset stored user information and the current user's information to the current text on the screen. If the current user is a preset storage user, add the current text on the screen with a watermark containing the preset stored user information; if the current user is detected When the text content belongs to the high sensitivity level among the preset sensitivity levels, the front camera of the terminal detects whether there is a camera device in the display area of the current text content.
  • step S10 it further includes:
  • the terminal collects an image at a first preset frequency, preprocesses the image, and determines whether the preprocessed image has a camera device, and if there is a camera device, it determines whether the image has a human face.
  • the preprocessing process is: deblurring the image, that is, using the Laplacian algorithm to identify the blurred image, and if the image is blurred, the detection of the image is abandoned.
  • the image is also grayed out or binarized.
  • the gray-scale processing is: use the RGB model to represent each pixel of the image, and take the average value of R, G, and B of each pixel to replace the original R, G, and B values to obtain the current image's grayscale Value; binarization processing is: divide the pixels of the image into two parts, black and white, black as foreground information, white as background information, in order to process the original image except for the target text other objects, Background etc.
  • the terminal also performs image noise reduction on the pictures, that is, filtering by means of median filtering, mean filtering, adaptive Wiener filtering, etc., to deal with the image noise caused by the process of image acquisition, compression, and transmission.
  • Step S20 Determine whether there is a camera device in the target display area according to a preset camera device recognition model and the first image of the display area;
  • the preprocessed image is input into the preset camera equipment recognition model.
  • the terminal pre-collects a large number of image data that exist in the terminal camera, video camera, or other types of camera equipment, and trains the above-mentioned image data as a training set to obtain the first preset camera equipment recognition model. That is, the K-nearest Neighbors (KNN) is used to classify the first image of the display area, and it is determined whether the first image of the display area has a camera device type image or does not have a camera device type image. Thus, it is determined whether there is an imaging device in the target display area.
  • KNN K-nearest Neighbors
  • Step S30 when there is a camera device in the target display area, perform corresponding encryption processing on the current device and/or current display information.
  • the terminal when the terminal detects that there is a camera device in the target display area that is aimed at the current text content, it turns off the current device or cancels the display of the current text content on the screen; if the terminal detects that there is a camera device that is not aimed at the current text content If yes, a prompt message is sent to the user, that is, the prompt message is "Camera equipment detected, beware of leaking sensitive information".
  • a preset encryption strategy corresponding encryption processing is performed on the current device and/or current display information.
  • This embodiment provides an encryption method for display information, by acquiring the target sensitivity level of the currently displayed information when the current device display information is monitored, and when the target sensitivity level reaches the preset sensitivity level, according to the first preset Frequency collection of the first image of the display area of the target display area corresponding to the current device; according to a preset camera device recognition model and the first image of the display area, it is determined whether there is a camera device in the target display area; When there is a camera device in the display area, corresponding encryption processing is performed on the current device and/or the current display information.
  • the present application recognizes the display area image corresponding to the current device through the camera device recognition model, that is, the display area image is classified through the KNN algorithm and the preset image type for real-time detection Whether there is a camera device that causes display information leakage in the display area of the current device.
  • FIG. 3 is a schematic flowchart of a second embodiment of a method for encrypting display information in this application.
  • the step S20 specifically includes:
  • Step S21 inputting the first image of the display area into the imaging device identification model, so as to output the classification result of the first image of the display area through the proximity algorithm KNN algorithm in the imaging device recognition model;
  • the preprocessed image is input to the first preset camera device recognition model (the terminal collects a large amount of image data of the terminal camera, video camera, or other types of camera devices in advance, and uses the above image data as a training set for training Obtain the first preset camera equipment recognition model), that is, use KNN (K-nearest Neighbors) algorithm.
  • KNN K-nearest Neighbors
  • the principal components analysis (PCA) is used for the picture to convert the image information into a vector table, and then the Euclidean distance is selected as the distance calculation method, and the vector corresponding to each type of image point is calculated.
  • the KNN algorithm is selected to select K points with the closest distance, and the distribution of K points in each type of image is determined.
  • the above-mentioned camera equipment design model can also be stored in a node of a blockchain.
  • step S21 specifically includes:
  • the first image of the display area is input to the imaging device identification model, and the first image of the display area is converted into image vector data based on the principal component analysis dimensionality reduction algorithm PCA dimensionality reduction algorithm in the imaging device recognition model ;
  • KNN K-nearest Neighbors
  • commonly used methods for measuring distance include: Euclidean distance, cosine value (cos), correlation, Manhattan distance, or others.
  • the K value of K is 1, once the nearest point is noise, then there will be a deviation, the K value
  • the decrease of means that the overall model becomes complicated and is prone to overfitting; if the value of K is too large, it is equivalent to predicting with training examples in a larger neighborhood, and the approximate error of learning will increase . At this time, instances far away from the input target point will also play a role in the prediction, making the prediction wrong.
  • the output result is "no camera equipment”, if it is “camera equipment”, you need to distinguish between “aligned to the screen” and “non-aligned to the screen”.
  • the first image of the display area is input to the imaging device identification model
  • the PCA dimensionality reduction algorithm is the first image of the display area based on the principal component analysis dimensionality reduction algorithm in the imaging device recognition model. Converted into image vector data; and then based on the Euclidean distance calculation formula and the image vector data, the first image of the display area and the camera device recognition model in the first image and the camera device recognition model are respectively calculated for the type image of the camera device and the type of the camera device that does not exist
  • the Euclidean distance between images based on the trained K value in the trained camera equipment recognition model, select the K points closest to the first image in the display area, and count the picture types belonging to the K points, which will be the most
  • the picture type determines the classification result of the first image in the display area.
  • Step S22 Determine whether there is an imaging device in the target display area according to the classification result of the first image in the display area.
  • the camera device exists or “the camera device does not exist"
  • FIG. 4 is a schematic flowchart of a third embodiment of a method for encrypting display information in this application.
  • the step S30 specifically includes:
  • Step S31 When there is a camera device in the target display area, determine whether there is a face image in the first image of the display area according to a preset face recognition model;
  • Step S32 If the face image exists in the first image of the display area, collect a second image of the display area of the target display area according to a second preset frequency, wherein the second preset frequency is greater than all the images.
  • Step S33 judging whether the facial emotion in the second image of the display area is the target facial emotion according to the preset emotion recognition model
  • Step S34 when the facial emotion in the second image of the display area is the target facial emotion, turn off the current display information of the current device to prevent leakage of display information.
  • a face recognition model that is, a face recognition model obtained by acquiring multiple face data for training
  • the terminal collects the second image of the display area at a second preset frequency, where the second preset frequency is greater than the first preset frequency. In this way, the terminal recognizes that there is a camera device in the image and there is a human face, which means that the current text content is at a high risk of leaking, and the image can be collected at a larger frequency, the recognition is more accurate, and the vigilance is increased.
  • emotion recognition is performed on the human face to obtain the recognition result, and corresponding security measures are taken according to the recognition result.
  • the emotion recognition model can be used to obtain the emotion recognition model by obtaining facial data containing multiple emotions. If the face in the image is a nervous emotion, it means that the current text content is very serious. Large risk of leakage, cancel the display of the current text content on the screen. In this way, more confidential measures can be taken to prevent information leakage.
  • step S30 specifically includes:
  • the imaging device When the imaging device is aimed at the currently displayed information, the currently displayed information of the current device is turned off to prevent the leakage of the displayed information.
  • the first preset camera device recognition model it is determined by the first preset camera device recognition model that the current text content is displayed in the display area of the camera device. Specifically, if there is a camera device, the second preset camera device recognition model is used to monitor whether the camera device is The text content is aligned. In the same way, the second preset camera device recognition model is obtained by pre-collecting a large amount of screen-aligned image data and non-aligned computer screen image data for training. Among them, the image is input to the second preset camera device recognition model, and emotion recognition is performed on the image at the same time, and an output result is obtained, that is, "the camera device is aligned with the current text content" or "the camera device is present but not aligned. The result of the current text content.
  • the embodiment of the present application also provides an encryption device for displaying information.
  • FIG. 5 is a schematic diagram of the functional modules of the first embodiment of the encryption device for displaying information of this application.
  • the encryption device for displaying information includes:
  • the first image acquisition module 10 is configured to acquire the target sensitivity level of the currently displayed information when the current device display information is monitored, and when the target sensitivity level reaches a preset sensitivity level, collect the The first image of the display area of the target display area corresponding to the current device;
  • the area equipment monitoring module 20 is configured to determine whether there is a camera device in the target display area according to a preset camera equipment recognition model and the first image of the display area;
  • the display information encryption module 30 is configured to perform corresponding encryption processing on the current device and/or current display information when there is a camera device in the target display area.
  • the regional equipment monitoring module 20 specifically includes:
  • An image classification unit configured to input the first image of the display area into the imaging device identification model to output the classification result of the first image of the display area through the proximity algorithm KNN algorithm in the imaging device recognition model ;
  • the device judging unit is configured to judge whether there is an imaging device in the target display area according to the classification result of the first image in the display area.
  • image classification unit is also used for:
  • the first image of the display area is input to the imaging device identification model, and the first image of the display area is converted into image vector data based on the principal component analysis dimensionality reduction algorithm PCA dimensionality reduction algorithm in the imaging device recognition model ;
  • the encryption device for displaying information further includes an image preprocessing module, and the image preprocessing module is used for:
  • the display information encryption module 30 is also used for:
  • a second image of the display area of the target display area is collected according to a second preset frequency, where the second preset frequency is greater than the first Preset frequency
  • the current display information of the current device is turned off to prevent the leakage of the display information.
  • the display information encryption module 30 is also used for:
  • the imaging device When the imaging device is aimed at the currently displayed information, the currently displayed information of the current device is turned off to prevent the leakage of the displayed information.
  • first image acquisition module 10 is also used for:
  • the currently displayed information is text information
  • extract keywords in the currently displayed information and determine the target sensitivity level of the currently displayed information according to the keywords
  • the target sensitivity level reaches the preset sensitivity level
  • the first image of the display area of the target display area corresponding to the current device is acquired according to the first preset frequency.
  • each module in the encryption device for displaying information corresponds to each step in the embodiment of the encryption method for displaying information, and its functions and implementation processes are not repeated here.
  • the embodiments of the present application also provide a computer-readable storage medium.
  • the computer-readable storage medium may be non-volatile or volatile.
  • the computer-readable storage medium of the present application stores an encryption program for display information, wherein when the encryption program for display information is executed by a processor, the steps of the encryption method for display information as described above are implemented.
  • the method implemented when the encryption program of the display information is executed can refer to the various embodiments of the encryption method of the display information of this application, which will not be repeated here.
  • the blockchain referred to in this application is a new application mode of computer technology such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with cryptographic methods. Each data block contains a batch of network transaction information for verification. The validity of the information (anti-counterfeiting) and the generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.
  • the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disks, optical disks), including several instructions to make a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of the present application.
  • a terminal device which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.

Abstract

Procédé, appareil et dispositif de chiffrement d'informations d'affichage, et support de stockage. Le procédé consiste à : lorsque des informations d'affichage d'un dispositif actuel sont détectées, acquérir un niveau de sensibilité cible des informations d'affichage actuelles, et lorsque le niveau de sensibilité cible atteint un niveau de sensibilité prédéfini, collecter, sur la base d'une première fréquence prédéfinie, une première image de région d'affichage d'une région d'affichage cible correspondant au dispositif actuel (S10) ; déterminer, sur la base d'un modèle d'identification de dispositif de caméra prédéfini et de la première image de région d'affichage, si un dispositif de caméra est présent dans la région d'affichage cible (S20) ; et dans la mesure où un dispositif de caméra est présent dans la région d'affichage cible, chiffrer le dispositif actuel et/ou les informations d'affichage actuelles (S30). De plus, en rapport également avec la technologie de chaîne de blocs, le modèle d'identification de dispositif de caméra peut être stocké dans une chaîne de blocs.
PCT/CN2020/102535 2020-04-30 2020-07-17 Procédé, appareil et dispositif de chiffrement d'informations d'affichage et support de stockage WO2021217899A1 (fr)

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