View data fuzzy reversible processing system and method based on national secret algorithm

Abstract

The invention relates to the technical field of image processing, in particular to a view data fuzzy reversible processing system and method based on a national cryptographic algorithm, and the system comprises a camera module, a processing module, a user module and a domestic cryptographic module. The camera module is used for acquiring original view data, and the camera module is communicated with the processing module through the domestic password module; the number of the processing modules is multiple, and the multiple processing modules are connected with the camera module and the user module. The user module is connected with the domestic password module, and the user module stores and reversibly processes the processed view data, the reversible fuzzy view processing is realized through the security service platform, and the problem of information loss caused by incapability of restoration is avoided while the privacy of other people is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a system and method for fuzzy reversible processing of view data based on a national secret algorithm. Background Art

[0002] Fuzzification refers to a method of view data processing, whose core purpose is to protect personal privacy and data security. Through fuzzification, personal identity information can be removed from the data, making it impossible to directly associate the processed data with a specific individual.

[0003] When the view is being blurred, the view to be processed is imported into the business platform, and the business platform blurs the sensitive information area, making it impossible for people to identify people through the processed view data, thereby ensuring that the privacy of others is not violated and the privacy security of others is guaranteed.

[0004] However, when blurring a view, one-way processing methods such as Gaussian blur and mosaic are usually used. When the original view needs to be viewed, the view data cannot be restored, resulting in the loss of important information features.

[0005] In view of this, we propose a fuzzy reversible processing system and method for view data based on the national secret algorithm. Summary of the invention

[0006] The purpose of the present invention is to provide a system and method for fuzzy reversible processing of view data based on a national secret algorithm, so as to solve the problem that the view data cannot be restored as mentioned in the above background technology.

[0007] To achieve the above purpose, the present invention provides the following technical solutions: a fuzzy reversible processing system and method for view data based on a national secret algorithm: The view data fuzzy reversible processing system based on the national cryptography algorithm includes a camera module, a processing module, a user module, and a domestic cryptography module; the camera module is used to obtain the original view data. The camera module can use a camera for shooting, and the camera conducts real-time shooting and monitoring of a specified area; the camera module is connected to the processing module through the domestic cryptography module; there are multiple processing modules, and multiple processing modules are all connected to the camera module and the user module. The domestic cryptography module is used to connect the camera module and the processing module, so that the original view data captured by the camera module is distributed to multiple processing modules. Each processing module runs independently and is respectively loaded on the corresponding edge computer. Each edge computer works independently and has an independent ID. The processing module on each edge computer receives different original view data and processes it. The processing module performs fuzzy processing on the original view data of the received pictures and videos and then transfers it to the user module for the user to view. The user views the blurred video pictures, protecting the privacy of others; The user module is connected to the domestic cryptography module. The user module stores and reversibly processes the processed view data. When it is necessary to view the pictures or videos clearly, the user module can be started through the domestic cryptography module for reversible view data processing to restore the original data and obtain the original photos and videos.

[0008] Preferably, the domestic cryptography module is divided into a national cryptography public key unit and a national cryptography private key unit; the national cryptography public key unit is used to connect the camera module and the processing module. The national cryptography public key unit contains multiple national cryptography public keys, and the national cryptography public keys correspond to the sub-processing modules one by one. Each national cryptography public key in the national cryptography public key unit corresponds to a processing module. The corresponding processing module is started through the one-to-one correspondence relationship. When the national cryptography public key unit is not started, the camera module is disconnected from each processing module, and the camera module stores the original view data of the captured pictures and videos in its own module. When the national cryptography public key unit is started, the camera module is connected to the processing module, and the camera module distributes the original view data stored in itself to each processing module, and the processing module processes the original view data; the national cryptography private key unit is connected to the user module, and the national cryptography private key unit is used to reversibly process the view data stored in the user module.

[0009] Preferably, the processing module includes an AI unit and a calculation unit; the AI unit is connected to the national cryptography public key unit. The AI unit receives, recognizes, and extracts generalized information from the original view data transmitted by the camera module. When the staff starts the national cryptography public key unit to input the national cryptography public key corresponding to this processing unit, the connection between the camera module and the AI unit of this processing module is established. The AI unit recognizes information such as faces, license plates, and document areas, and at the same time, extracts information such as gender, age group, and license plate information. The calculation unit is respectively connected to the AI unit, the national cryptography public key unit, and the user module. The calculation module receives the data extracted by the AI unit and performs blurring calculation processing on the view data. The calculation module retrieves the national cryptography algorithm through the national cryptography public key unit, and calculates the exclusive blurring factor λ according to its corresponding national cryptography public key through the national cryptography algorithm, and combines the blurring factor λ with the view data extracted by the AI unit for calculation to perform blurring processing on the original view data.

[0010] Preferably, the user module includes a permission determination unit, a viewing unit, and an inverse calculation unit; the permission determination unit is respectively connected to the viewing unit and the national cryptography private key unit. When a user logs in to the user module, the permission determination unit is activated to determine the permission level of the logged-in user. If the user is an ordinary user, it jumps to the viewing unit, and the viewing unit is partially opened for ordinary users to view. If the user is a key user, the national cryptography private key unit is started, and the viewing unit is accessed through the national cryptography private key unit to expand the viewing range. The viewing unit is respectively connected to the calculation unit and the inverse calculation unit. The calculation unit transmits the blurred view data to the viewing unit for the user to view. The blurred view data includes: anonymized view data, the edge computing device ID loaded by the current processing module, the blurring area coordinate, and the generalized information. The viewing unit is connected to the national cryptography private key unit, and the national cryptography private key unit is connected to the inverse calculation unit; the inverse calculation unit is used for restoring the original view data. When the national private key unit is started, the viewing unit is connected to the inverse calculation unit. The national cryptography algorithm is called through the national private key unit to obtain the eigenvalue. At the same time, the view data in the viewing unit is read, and the eigenvalue is combined with the view data for inverse operation to obtain the original view data.

[0011] A method for reversibly blurring view data includes the following steps: Step 1, the camera module acquires the original view data; The camera module takes pictures and videos through the camera, thereby obtaining the original view data and storing the original view data in its own module. Step 2, the staff connects the camera module and the processing module through the national cryptography public key unit; The staff logs in to the corresponding processing module through the national cryptography public key in the national cryptography public key unit, enabling the processing module to communicate with the camera module. The camera module distributes the original view data stored in itself to the started processing module; Step 3: The processing module receives the original data and performs reversible blurring processing on the original data; The processing module blurs the sensitive data in the original view data, thereby ensuring the privacy of others; Step 4: The processing module transmits the view data after the reversible blurring processing to the user module; The processing module performs blurring processing on the received original view data and transmits the blurred view data to the user module for the user to log in and view; Step 5: The user logs in to the user module, and the user module displays the view data in grades according to the logged-in user's permissions; According to the permission level of the user's login account, the user can perform view data access and processing operations to different extents.

[0012] Preferably, the said Step 3 includes the following steps: Step 3.1: The AI unit receives the original view data; The original view data is transmitted into the processing module, and the AI unit receives the original view data one by one; Step 3.2: The AI unit identifies the original view data and extracts generalization information; The AI unit performs face recognition on the received original view data, thereby judging the gender and age range of the person. At the same time, license plate and certificate information is extracted to obtain license plate and certificate information; Step 3.3: The AI unit transmits the identified and extracted data to the calculation unit; The AI unit directly transmits the extracted generalization information into the calculation unit; Step 3.4: The calculation unit performs reversible blurring processing through the national cryptography public key unit; The calculation unit retrieves the national cryptography algorithm through the national cryptography public key unit to obtain a dedicated blurring factor λ and combines the extracted generalization information to perform blurring processing on the original view data, thereby ensuring the privacy of the person photographed by the camera module and avoiding the exposure of private features; Step 3.5: The calculation unit transmits the processed view data to the user module for storage; The blurred view data is transmitted into the user module for storage and provided for the user to view.

[0013] Preferably, the said Step 3.4 includes the following steps: Step 3.4.1: The calculation unit divides the view data into grids, The calculation unit divides the view into grids, which facilitates the coordinate positioning of the area to be blurred, and then realizes precise processing through the calculation unit, improving the blurring efficiency; Step 3.4.2: The calculation unit retrieves the national cryptography algorithm through the national cryptography public key unit and calculates the exclusive blurring factor λ; The calculation unit accesses the national cryptography public key unit to retrieve the national cryptography algorithm in the national cryptography public key unit, imports its own exclusive national cryptography public key into the national cryptography algorithm, and calculates the exclusive blurring factor λ of the calculation unit through the national cryptography algorithm; Step 3.4.3: The calculation unit performs DCT transformation based on the exclusive blurring factor λ to blur the grid of the specified area; The calculation unit combines the blurring factor λ and the extracted data information to perform DCT transformation to blur the sensitive information area.

[0014] Preferably, the said step 5 includes the following steps: Step 5.1: The user logs in to the user module; When it is necessary to view the blurred view data, the user logs in to the user module through his own exclusive account; Step 5.2: The permission determination unit determines the user's permission The permission determination module judges the level of permission according to the user's account, and determines whether the user is an ordinary user or a key user; Step 5.3: If it is an ordinary user, only partial view data in the viewing unit can be viewed; If the permission determination module detects that the user account is an ordinary user, the user can only view the processed anonymous view data; Step 5.4: If it is a key user, the data in the viewing unit can be restored through the inverse calculation unit; If the permission determination module detects that the user account is a key user, the user can view the blurred view data and can also restore the blurred view data to view the original view data.

[0015] Preferably, the said step 5.4 includes the following steps: Step 5.4.1: The key user activates the national cryptography private key unit to connect the viewing unit and the inverse calculation unit; The key user retrieves the national cryptography private key unit and inputs his own national cryptography private key. The national cryptography private key releases the content of the viewing unit for the key user to view. At the same time, the inverse calculation unit is activated and can extract the data in the viewing unit; Step 5.4.1: The inverse calculation unit calculates the exclusive blurring factor λ through the national cryptography algorithm; The inverse calculation unit retrieves the national cryptography algorithm using the national cryptography private key of the key user, and calculates the exclusive fuzzy factor λ according to the national cryptography algorithm; Step 5.4.1, the inverse calculation unit retrieves the fuzzy view data in the retrieval unit and performs IDCT calculation in combination with the exclusive fuzzy factor λ; The inverse calculation unit performs IDCT transformation on the exclusive fuzzy factor λ and the fuzzy view data, and then restores the original view; Step 5.4.1, the inverse calculation unit restores the fuzzy view data to the original view data for the key user to view; The restored original view is provided for the key user to view to obtain all the information in the data.

[0016] Preferably, the key users are divided into high-level key users and ordinary key users; the high-level key users can restore the fuzzy view data of all regions; the ordinary key users can restore the fuzzy view data of the current region; The high-level key users hold high-level keys, such as public security and management departments, and can restore all fuzzy view data. The ordinary key users hold ordinary keys, such as the views of ordinary departments and units, and can restore the fuzzy view data of their own departments and units.

[0017] Compared with the prior art, the beneficial effects of the present invention are: 1. For the view data fuzzy reversible processing system and method based on the national cryptography algorithm, the present invention realizes the processing of reversible fuzzy views through the security service platform, ensuring the privacy of others while avoiding the problem of information loss caused by irreversibility.

[0018] 2. For the view data fuzzy reversible processing system and method based on the national cryptography algorithm, the present invention realizes the reversible processing of fuzzy view data through this processing method, meets the viewing requirements in different situations, protects the privacy information of others, and at the same time avoids the loss of key information.

[0019] 3. For the view data fuzzy reversible processing system and method based on the national cryptography algorithm, the present invention realizes multi-level viewing through this processing method, ensures the privacy and security of view data, avoids the leakage of view data, and protects the privacy information of others. Description of the Drawings

[0020] Figure 1 It is the overall framework diagram of the view data fuzzy reversible processing system of the present invention; Figure 2 It is the flow framework diagram of the view data fuzzy reversible processing method of the present invention; Figure 3 It is the inverse processing flow chart of the view data of the present invention.

[0021] In the figure: 1. Camera module; 2. Processing module; 21. AI unit; 22. Calculation unit; 3. User module; 31. Permission determination unit; 32. Access unit; 33. Inverse calculation unit; 4. Domestic cipher module; 41. National cipher public key unit; 42. National cipher private key unit. Specific implementation manner

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] When it is necessary to monitor a certain target, the camera will take pictures of the monitored person and display the captured view for viewing. However, when the camera takes pictures of the monitored person, it will also capture non-monitored targets. When it is necessary to view the view, the non-monitored targets will also be displayed, exposing the information of the non-monitored targets and thus causing the leakage of privacy information. Therefore, it is necessary to perform blurring processing to ensure the privacy of others.

[0024] During the process of blurring the view data, the view data to be processed is imported into the processing platform, and the processing platform performs blurring processing on the sensitive information area, so that people cannot identify the person through the processed view data, ensuring that the privacy of others is not violated and the privacy security of others is guaranteed.

[0025] However, when blurring the view, usually one-way processing methods such as Gaussian blurring and mosaic are used for blurring processing. When it is necessary to view the original view, the view data cannot be restored, resulting in the loss of important information features. A technical solution provided by the present invention: A system and method for reversibly blurring view data based on the national cipher algorithm: As Figure 1 shown, a system for reversibly blurring view data based on the national cipher algorithm is characterized in that it includes a camera module 1, a processing module 2, a user module 3, and a domestic cipher module 4; the camera module 1 is used to obtain the original view data, and the camera module 1 is connected to the processing module 2 through the domestic cipher module 4; there are multiple processing modules 2, and multiple processing modules 2 are all connected to the camera module 1 and the user module 3; the user module 3 is connected to the domestic cipher module 4, and the user module 3 stores and reversibly processes the processed view data. Specifically, the camera module 1 is the original data acquisition end. The camera module 1 can use a camera to take pictures and videos, thereby obtaining the original view data. The original data module collected by the camera is temporarily stored in the camera module 1. When the staff starts the processing module 2 through the national cryptography unit, the camera module 1 distributes the collected data into the processing module 2. There are multiple processing modules 2, and each processing module 2 is loaded on the corresponding edge computer. Each edge computer has a corresponding ID address and a national cryptography unit for starting the processing unit loaded on itself. The edge computers work independently, so that each processing module 2 works independently. When multiple processing modules 2 are activated under the action of the national cryptography unit and connected to the camera module 1, the camera module 1 distributes the original view data stored in itself to each processing module 2. The processing module 2 performs blurring processing on the sensitive view data in the original view data received by itself, thereby ensuring that the privacy of others is not violated. The processed blurred view data is sent to the user module 3 for the user to view under specific circumstances. When necessary, the original view data can be restored from the blurred view data through the national cryptography unit for the user to view; Preferably, the edge computer is a computer of the prior art. Each edge computer has its corresponding ID address. The edge computers are distributed near the camera, thereby forming an edge computing gateway to anonymize the view data source and prevent the disorderly diffusion of the original view data.

[0026] In this embodiment, the domestic cryptography module 4 is divided into a national public key unit 41 and a national private key unit 42; the national public key unit 41 is used to connect the camera module 1 and the processing module 2. The national public key unit 41 contains multiple national public keys, and the national public keys correspond to the sub-processing modules 2 one by one; the national private key unit 42 is connected to the user module 3; Specifically, the domestic cryptography module 4 is divided into a national public key unit 41 and a national private key unit 42. The national public key unit 41 is used by the staff to activate the processing module 2 loaded on the edge computer, so that the processing module 2 is connected to the camera module 1 to receive the original view data; the national private key unit 42 is used to activate the user's permission in the user module 3 to realize the restoration processing of the blurred view data.

[0027] Preferably, the national public key unit 41 contains multiple national public keys, and each national public key has a corresponding processing module 2, so that the national public keys correspond to the processing modules 2 one by one, ensuring that each processing module 2 has a unique corresponding national public key.

[0028] In this embodiment, the processing module 2 includes an AI unit 21 and a computing unit 22; the AI unit 21 is connected to the national cryptographic public key unit 41, and the AI unit 21 receives, identifies, and extracts generalization information from the original view data transmitted by the camera module 1; the computing unit 22 is respectively connected to the AI unit 21, the national cryptographic public key unit 41, and the user module 3, and the computing module receives the data extracted by the AI unit 21 and performs fuzzy calculation processing on the view data. Specifically, the AI unit 21 is used to analyze and extract the original view data. When the processing module 2 is connected to the camera module 1 under the action of the national cryptographic public key unit 41, the camera module 1 sends the original view data to the processing module 2. The AI unit 21 in the processing module 2 analyzes the original view data to obtain the generalization information in the original view. The AI unit 21 transmits the extracted generalization information to the computing unit 22. The computing unit 22 performs grid division on the original view data to obtain the regional coordinates where the generalization information is located. The computing unit 22 retrieves the national cryptographic algorithm in the national cryptographic public key unit 41, obtains its own exclusive fuzzy factor λ by combining its own exclusive national cryptographic public key, and performs fuzzy calculation on the exclusive fuzzy factor λ, the coordinates of the area to be blurred, and the edge computer ID to obtain anonymized view data. The anonymized view data, the exclusive fuzzy factor λ, the coordinates of the area to be blurred, and the edge computer ID are stored in the user unit as the blurred view data. Preferably, the exclusive fuzzy factor λ obtained by combining the national cryptographic algorithm with the national cryptographic public key ensures the uniqueness and security of λ and prevents reverse cracking.

[0029] In this embodiment, the user module 3 includes a permission determination unit 31, a viewing unit 32, and an inverse calculation unit 33; the permission determination unit 31 is respectively connected to the viewing unit 32 and the national cryptographic private key unit 42; the viewing unit 32 is respectively connected to the computing unit 22 and the inverse calculation unit 33, the viewing unit 32 is connected to the national cryptographic private key unit 42, and the national cryptographic private key unit 42 is connected to the inverse calculation unit 33; the inverse calculation unit 33 is used for restoring the original view data. Specifically, the permission determination unit 31 is used to determine the permission level of the user logging into the account of user module 3. When a user logs into user module 3, the permission determination unit 31 is activated to determine the permission level of the logged-in user. If the user is an ordinary user, only the anonymized view data in the query unit 32 is available for the ordinary user to view, thus ensuring the privacy information of others. If the user is a key user, the national cryptography private key unit 42 is activated. When the national cryptography private key unit 42 accesses the query unit 32, the fuzzy view data can be viewed. If the user needs to restore the fuzzy view data, the user activates the inverse calculation unit 33. The inverse calculation unit 33 retrieves the national cryptography algorithm through the national private key unit, calculates the exclusive fuzzy factor λ in combination with the national private key, and the inverse calculation unit 33 performs ICDT transformation calculation on the exclusive fuzzy factor and the fuzzy view data to restore the original view data; Preferably, the key user has a national cryptography private key uniquely corresponding to their own account.

[0030] Figure 1 This is the overall framework diagram of the fuzzy reversible processing system for view data of the present invention. This diagram is detailedly shown through the introduction of the overall framework of the single processing module 2. The camera module 1 collects the original view data. The national cryptography public key unit 41 connects the camera module 1 and the processing module 2. The camera module 1 distributes the collected original view data to the AI unit 21. The AI unit 21 extracts the original data and transfers the extracted information to the calculation unit 22. The calculation unit 22 calculates the fuzzy factor according to the national cryptography public key unit 41, and performs DCT transformation on the fuzzy factor and the extracted information to obtain the fuzzy view data for the user to view. Ordinary users can only view the anonymized view data in the fuzzy view data. Key users can view the entire fuzzy view and restore the fuzzy view data through the national cryptography private key unit 42.

[0031] As Figures 2 to 3 shown, a method for fuzzy reversible processing of view data includes the following steps: Step 1: The camera module 1 obtains the original view data; Step 2: The staff connects the camera module 1 and the processing module 2 through the national cryptography public key unit 41; Step 3: The processing module 2 receives the original data and performs reversible fuzzy processing on the original data; Step 4: The processing module 2 transmits the view data after the reversible fuzzy processing to the user module 3; Step 5: The user logs into the user module 3, and the user module 3 hierarchically displays the view data according to the logged-in user's permissions; Specifically, the camera module 1 takes pictures and videos through a camera to obtain original view data, and temporarily stores the original view data in its own module. The staff starts the national secret public key unit 41 through the edge computer and enters the corresponding national secret public key to log in to the corresponding processing module 2, so that the processing module 2 is connected to the camera module 1. The camera module 1 distributes the original view data stored in itself to the started processing module 2. The processing module 2 blurs the sensitive data in the original view data to ensure the privacy of others. The processing module 2 blurs the received original view data and transmits the blurred view data to the user module 3 for the user to log in and view. According to the authority level of the user login account, the user can perform different degrees of view data viewing and processing operations.

[0032] In this embodiment, step 3 includes the following steps: Step 3.1, the AI unit 21 receives original view data; Step 3.2, the AI unit 21 identifies the original view data and extracts generalized information; Step 3.3, the AI unit 21 transmits the identified and extracted data to the computing unit 22; Step 3.4, the calculation unit 22 performs reversible obfuscation processing through the national secret public key unit 41; Step 3.5, the computing unit 22 transmits the processed view data to the user module 3 for storage; Specifically, the original view data is transmitted to the processing module 2, and the AI unit 21 receives the original view data one by one. The AI unit 21 performs face recognition on the received original view data, and then determines the gender and age group of the person. At the same time, the license plate and certificate information are extracted to obtain the license plate and certificate information. The AI unit 21 directly transmits the extracted generalized information to the calculation unit 22. The calculation unit 22 uses the national secret algorithm through the national secret public key unit 41 to combine with its own national secret public key to obtain a dedicated fuzzy factor λ, and combines the fuzzy factor λ with the extracted generalized information to confirm the area to be blurred, that is, the sensitive information area, and then fuzzifies the original view data to obtain anonymized view data, thereby ensuring the privacy of the person photographed by the camera module 1 and avoiding the exposure of private features. The anonymized view data, the edge computer ID, the fuzzy area coordinates and the generalized information are transmitted to the user module 3 as fuzzy view data for storage and for user review, wherein the anonymization is for ordinary users to review; Preferably, the extraction of generalized information retains non-sensitive attributes, such as gender, age range, etc., to support data analysis without exposing individual characteristics.

[0033] In this embodiment, step 3.4 includes the following steps: Step 3.4.1: The calculation unit 22 performs grid division on the view data; Step 3.4.2: The calculation unit 22 retrieves the national cryptography algorithm through the national cryptography public key unit 41 and calculates the exclusive fuzzy factor λ; Step 3.4.3: The calculation unit 22 performs DCT transformation based on the exclusive fuzzy factor λ to blur the grids in the specified area; Specifically, the calculation unit 22 combines the generalization information extracted by the AI unit 21 to confirm the sensitive information area. The calculation unit 22 performs grid division on the view to facilitate coordinate positioning of the sensitive information area, and then realizes precise processing through the calculation unit 22, improving the fuzzy processing efficiency. Combining the grid division to obtain the coordinates of the fuzzy area, the calculation unit 22 accesses the national cryptography public key unit 41 to retrieve the national cryptography algorithm in the national cryptography public key unit 41, and imports its own exclusive national cryptography public key into the national cryptography algorithm. Through the national cryptography algorithm, the exclusive fuzzy factor λ of the calculation unit 22 is calculated. The calculation unit 22 combines the fuzzy factor λ and the extracted data information to perform DCT transformation to blur the sensitive information area to obtain anonymized view data; Preferably, Fλ = DCT(f(i,j)) * λ f(i,j): Spatial domain coordinates (i,j) of the fuzzy area.

[0034] λ: Fuzzy factor calculated using the national cryptography algorithm.

[0035] In this embodiment, the step 5 includes the following steps: Step 5.1: The user logs in to the user module 3; Step 5.2: The permission determination unit 31 determines the user's permission; Step 5.3: If it is an ordinary user, only part of the view data in the viewing unit 32 can be viewed; Step 5.4: If it is a key user, the data in the viewing unit 32 can be restored through the inverse calculation unit 33; Specifically, when it is necessary to view the fuzzy view data, the user logs in to the user module 3 through their own exclusive account. The permission determination module judges the level of permission according to the user's account to determine whether the user is an ordinary user or a key user. If the permission determination module detects that the user account is an ordinary user, the user can only view the anonymized view data and cannot view other information. If the permission determination module detects that the user account is a key user, the user can view the blurred view data and can also restore the blurred view data to view the original view data; In this embodiment, the step 5.4 includes the following steps: Step 5.4.1: The key user activates the national cryptography private key unit 42 to connect the viewing unit 32 and the inverse calculation unit 33; Step 5.4.1: The inverse calculation unit 33 calculates the exclusive fuzzy factor λ through the national cryptography algorithm. Step 5.4.1: The inverse calculation unit 33 retrieves the fuzzy view data in the retrieval unit 32 and performs IDCT calculation in combination with the exclusive fuzzy factor λ. Step 5.4.1: The inverse calculation unit 33 restores the fuzzy view data to the original view data for the key user to view. Specifically, the key user calls out the national cryptography private key unit 42 and inputs its own national cryptography private key. The national cryptography private key unlocks the content in the retrieval unit 32 for the key user to retrieve. At the same time, the inverse calculation unit 33 is activated and can extract the data in the retrieval unit 32. At the same time, the inverse calculation unit 33 retrieves the national cryptography algorithm through the national cryptography private key of the key user and calculates the exclusive fuzzy factor λ according to the national cryptography algorithm. The inverse operation unit combines the exclusive fuzzy factor λ with the fuzzy region coordinates and edge calculation ID to perform IDCT transformation, thereby inversely inferring the fuzzy view data, obtaining the original view data, and restoring the completed original view for the key user to view, obtaining all the information in the data and avoiding the loss of key information. Preferably, f(i,j) = IDCT(Fλ / λ) DCT and IDCT are inverse to each other. IDCT realizes the conversion of the fuzzy block back to the original pixel block and stitches them into a complete image.

[0036] In this embodiment, the key users are divided into high-level key users and ordinary key users; the high-level key users can restore the fuzzy view data of all regions; the ordinary key users can restore the fuzzy view data of the current region. Specifically, high-level key users hold high-level keys, such as public security and management departments, and can restore all fuzzy view data. Ordinary key users hold ordinary keys, such as the views of ordinary departments and units, and can restore the fuzzy view data of their own departments and units.

[0037] Figure 2 This is the flowchart framework of the fuzzy reversible processing method for view data of the present invention. This flowchart details the processing method of view data, performs generalization information collection on the obtained original view data, obtains the area of sensitive information, performs grid division, obtains the coordinates of the sensitive information area, and prepares to perform fuzzy processing on this area. At the same time, retrieves the national cryptography public key to obtain the fuzzy factor, performs DCT transformation on the fuzzy factor and the extracted information to obtain the fuzzy view data for the user to view. Ordinary users can only view the anonymous view data in the fuzzy view data, and key users can view the entire fuzzy view and restore the fuzzy view data through the national cryptography private key unit 42.

[0038] Figure 3It is the reverse processing flowchart of the view data of the present invention, which details the process of restoring the blurred view data to the original view data. First, the blur factor is obtained through the national cryptography private key unit 42, and then the edge computer ID and the coordinates of the blurred area are subjected to IDCT transformation together with the anonymous view data to obtain the original view data.

[0039] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions in the specification are only the preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A view data fuzzy reversible processing system based on national cryptographic algorithms, characterized in that: It includes a camera module (1), a processing module (2), a user module (3), and a domestic cipher module (4); The camera module (1) is used to obtain original view data, and the camera module (1) is connected to the processing module (2) through the domestic cipher module (4); There are multiple processing modules (2), and multiple processing modules (2) are all connected to the camera module (1) and the user module (3); The user module (3) is connected to the domestic cipher module (4), and the user module (3) stores and reversibly processes the processed view data.

2. The system according to claim 1, wherein: The domestic cipher module (4) is divided into a national cipher public key unit (41) and a national cipher private key unit (42); The national cipher public key unit (41) is used to connect the camera module (1) and the processing module (2). The national cipher public key unit (41) contains multiple national cipher public keys, and the national cipher public keys correspond to the sub-processing modules (2) one by one; The national cipher private key unit (42) is connected to the user module (3).

3. The system according to claim 2, wherein: The processing module (2) includes an AI unit (21) and a computing unit (22); The AI unit (21) is connected to the national cipher public key unit (41), and the AI unit (21) receives, identifies, and extracts generalization information from the original view data transmitted by the camera module (1); The computing unit (22) is respectively connected to the AI unit (21), the national cipher public key unit (41), and the user module (3). The computing module receives the data extracted by the AI unit (21) and performs view data blurring calculation processing.

4. The system according to claim 2, characterized in that: The user module (3) includes an authority determination unit (31), a viewing unit (32), and an inverse calculation unit (33); The authority determination unit (31) is respectively connected to the viewing unit (32) and the national cipher private key unit (42); The viewing unit (32) is respectively connected to the computing unit (22) and the inverse calculation unit (33). The viewing unit (32) is connected to the national cipher private key unit (42), and the national cipher private key unit (42) is connected to the inverse calculation unit (33); The inverse calculation unit (33) is used for restoring the original view data.

5. A method for blurring and reversibly processing view data, which is used in the view data blurring and reversibly processing system according to any one of the above claims 1-4, characterized in that, It includes the following steps: Step 1, the camera module (1) obtains original view data; Step 2, the staff connects the camera module (1) and the processing module (2) through the national cipher public key unit (41); Step 3, the processing module (2) receives the original data and performs reversible blurring processing on the original data; Step 4, the processing module (2) transmits the view data after the reversible blurring processing to the user module (3); Step 5, the user logs in to the user module (3), and the user module (3) hierarchically displays the view data according to the logged-in user's authority.

6. The method according to claim 5, wherein: The said Step 3 includes the following steps: Step 3.1, the AI unit (21) receives the original view data; Step 3.2, the AI unit (21) identifies the original view data and extracts generalization information; Step 3.3, the AI unit (21) transmits the identified and extracted data to the computing unit (22); Step 3.4, the computing unit (22) performs reversible blurring processing through the national cipher public key unit (41); Step 3.5: The computing unit (22) transfers the processed view data to the user module (3) for storage.

7. The method according to claim 6, characterized in that: The said step 3.4 includes the following steps: Step 3.4.1: The computing unit (22) divides the view data into grids. Step 3.4.2: The computing unit (22) retrieves the national cryptography algorithm through the national cryptography public key unit (41) to calculate the exclusive fuzzy factor λ. Step 3.4.3: The computing unit (22) performs DCT transformation based on the exclusive fuzzy factor λ to blur the grids in the specified area.

8. The method according to claim 5, wherein: The said step 5 includes the following steps: Step 5.1: The user logs in to the user module (3). Step 5.2: The permission determination unit (31) determines the user's permission. Step 5.3: If it is an ordinary user, only partial view data in the viewing unit (32) can be viewed. Step 5.4: If it is a key user, the inverse computing unit (33) can restore the data in the viewing unit (32).

9. The method according to claim 8, characterized in that: The said step 5.4 includes the following steps: Step 5.4.1: The key user activates the national cryptography private key unit (42) to connect the viewing unit (32) and the inverse computing unit (33). Step 5.4.1: The inverse computing unit (33) calculates the exclusive fuzzy factor λ through the national cryptography algorithm. Step 5.4.1: The inverse computing unit (33) retrieves the blurred view data in the viewing unit (32) and performs IDCT calculation in combination with the exclusive fuzzy factor λ. Step 5.4.1: The inverse computing unit (33) restores the blurred view data to the original view data for the key user to view.

10. The method according to claim 9, characterized in that: The said key users are divided into high-level key users and ordinary key users; The high-level key users can restore the blurred view data of all regions; The ordinary key users can restore the blurred view data of the current region.

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