LCD safety protection system based on encryption processing

Abstract

The invention provides a liquid crystal display (LCD) security protection system based on encryption processing, which relates to the field of security protection and is characterized in that an AES128 fixed key is burnt to an LCD panel and stored in a tamper-proof area of a security chip on a key management layer. The controller and the LCD panel perform handshake interaction to generate a dynamic encrypted initial vector which has unpredictability and defines a period of validity of 30 seconds. And in a data encryption layer, a paging heartbeat data structure design is adopted to carry out data composite encryption so as to obtain a ciphertext. And then, decrypting and verifying the ciphertext through the LCD panel, and determining an execution action. Therefore, through key storage hardware, initial vector dynamics and data structure randomization, an LCD communication protection system which has a multi-level dynamic encryption mechanism and adapts to a high-security scene is constructed, and the defects that a static key is easy to leak, an initial vector is predictable and the replay attack resistance is weak are overcome.

Description

Technical Field

[0001] This application relates to the field of security protection, and more particularly, in the embodiments of this application, it relates to an LCD security protection system based on encryption processing. Background Art

[0002] With the wide application of liquid crystal display (LCD) modules in key fields such as financial terminals, industrial control devices, and intelligent security systems, the security issue of its data transmission channel has become increasingly prominent. In scenarios involving sensitive information interaction, the LCD module not only undertakes the function of the human-machine interface, but also becomes an important target for attackers to carry out side-channel attacks, data tampering, or spoofing communications.

[0003] Traditional security protection schemes mostly use a single encryption algorithm to protect display data, but in practical applications, they expose systematic defects such as easy leakage of static keys, predictability of initial vectors, and weak anti-replay attack capabilities. For example, the fixed key is stored in the general-purpose memory for a long time, resulting in the risk of physical extraction. The lack of a dynamic update mechanism for the encryption initial vector (IV) allows attackers to crack the encryption mode through statistical analysis methods. And a simple verification mechanism is difficult to resist man-in-the-middle attacks launched through reverse engineering.

[0004] Therefore, an optimized LCD security protection scheme based on encryption processing is desired. Summary of the Invention

[0005] To solve the above technical problems, this application is proposed. The embodiments of this application provide an LCD security protection system based on encryption processing. First, at the key management level, the AES128 fixed key is burned into the LCD board and stored in the tamper-proof area of the security chip. Then, through the handshake interaction between the controller and the LCD board, a dynamic encryption initial vector with unpredictability and a validity period of 30 seconds is generated. And at the data encryption level, a paged heartbeat data structure design is adopted for data composite encryption to obtain ciphertext. Then, the LCD board decrypts and verifies the ciphertext and determines the execution action. In this way, through the hardwareization of key storage, the dynamicization of the initial vector, and the randomization of the data structure, an LCD communication protection system suitable for high-security scenarios with a multi-level dynamic encryption mechanism is constructed, improving the defects of easy leakage of static keys, predictability of the initial vector, and weak anti-replay attack capabilities.

[0006] According to one aspect of the present application, a security protection system for LCD based on encryption processing is provided, which includes: a key fixed storage module for burning an AES128 fixed key through an LCD board and storing it in the tamper-proof area of a security chip; an encryption initial vector acquisition module for acquiring a dynamic encryption initial vector through a controller; a heartbeat data encryption module for generating heartbeat data through the controller and performing composite encryption on the heartbeat data to obtain ciphertext; a decryption verification module for decrypting and verifying the ciphertext through the LCD board to obtain a decryption result after receiving the ciphertext; and an execution action module for determining an execution action based on the decryption result.

[0007] Compared with the prior art, the security protection system for LCD based on encryption processing provided by the present application first burns the AES128 fixed key to the LCD board and stores it in the tamper-proof area of the security chip at the key management level. Then, a dynamic encryption initial vector with unpredictability and a validity period of 30 seconds is generated through handshake interaction between the controller and the LCD board. And at the data encryption level, a paged heartbeat data structure design is adopted for data composite encryption to obtain ciphertext. Next, the LCD board decrypts and verifies the ciphertext and determines the execution action. In this way, through the hardwareization of key storage, the dynamicization of the initial vector, and the randomization of the data structure, an LCD communication protection system suitable for high-security scenarios with a multi-level dynamic encryption mechanism is constructed, improving the defects of easy leakage of static keys, predictability of the initial vector, and weak anti-replay attack ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0009] Figure 1 It is a system block diagram of a security protection system for LCD based on encryption processing according to an embodiment of the present application.

[0010] Figure 2 It is a block diagram of a heartbeat data encryption module in a security protection system for LCD based on encryption processing according to an embodiment of the present application.

[0011] Figure 3 It is a block diagram of a ciphertext generation unit in a security protection system for LCD based on encryption processing according to an embodiment of the present application.

[0012] Figure 4Block diagram of a primary encryption subunit in an LCD security protection system based on encryption processing according to an embodiment of the present application. Detailed implementation manners

[0013] Various exemplary embodiments, features, and aspects of the present application will be described in detail below with reference to the accompanying drawings. Identical reference numerals in the drawings denote elements having the same or similar functions. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0014] The term "exemplary" used herein means "serving as an example, embodiment, or illustration". Any embodiment described as "exemplary" herein is not necessarily to be construed as superior or better than other embodiments.

[0015] In addition, for a better description of the present application, numerous specific details are given in the following detailed implementation manners. Those skilled in the art should understand that the present application can also be implemented without some specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art are not described in detail so as to highlight the gist of the present application.

[0016] Furthermore, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0017] With the wide application of LCD modules in financial terminals, industrial control devices, and intelligent security systems, the security of their data transmission channels has become a key issue. Traditional security solutions usually rely on a single encryption algorithm to protect display data, but there are defects such as easy leakage of static keys, predictable initial vectors, and weak anti-replay attack capabilities, increasing the risk of attacks through physical extraction, statistical analysis, reverse engineering, etc. Existing protection measures are difficult to fully guarantee data security in scenarios involving sensitive information interaction.

[0018] In view of the above technical problems, the present application proposes an LCD security protection system based on encryption processing. Figure 1 System block diagram of an LCD security protection system based on encryption processing according to an embodiment of the present application. As Figure 1As shown in the figure, the LCD security protection system 100 based on encryption processing according to an embodiment of the present application includes: a key fixed storage module 110, configured to burn an AES128 fixed key through an LCD board and store it in the tamper-proof area of a security chip; an encryption initial vector acquisition module 120, configured to acquire a dynamic encryption initial vector through a controller; a heartbeat data encryption module 130, configured to generate heartbeat data through the controller and perform composite encryption on the heartbeat data to obtain a ciphertext; a decryption verification module 140, configured to decrypt and verify the ciphertext through the LCD board to obtain a decryption result after receiving the ciphertext; and an execution action module 150, configured to determine an execution action based on the decryption result.

[0019] This technical solution effectively addresses the key defects of traditional LCD security solutions through a multi-level dynamic encryption mechanism. At the key management level, the AES128 fixed key is burned into the LCD board and stored in the tamper-proof area of the security chip, which not only blocks key extraction attacks through hardware physical protection but also avoids the risk of leakage of keys stored in general-purpose memories for a long time. Regarding the predictability problem of the initial vector, a dynamic encryption initial vector is generated through handshake interaction between the controller and the LCD board. The dynamic encryption initial vector formed by the true random number recombination technology is unpredictable, and the ring buffer storage mechanism with a 30-second validity period fundamentally eliminates the possibility of replay attacks. At the data encryption level, a paged heartbeat data structure design is adopted. Through differential fixed identification byte configuration and double true random number injection, the encrypted data packet has dynamic change characteristics, and the fixed key and the dynamic encryption initial vector are subjected to composite encryption, which not only maintains the efficiency of the encryption algorithm but also destroys the statistical regularity of the encryption mode through dynamic elements, significantly enhancing the protection ability against man-in-the-middle attacks and pattern recognition cracking. The overall solution constructs an LCD communication protection system suitable for high-security scenarios through triple protection of hardware-based key storage, dynamic initial vector, and randomized data structure.

[0020] In the above-mentioned LCD security protection system 100 based on encryption processing, the key fixed storage module 110 is used to burn the AES128 fixed key through the LCD board and store it in the tamper-proof area of the security chip. It should be understood that in the traditional LCD security system, the key storage link often becomes the weakest breakthrough point in the entire encryption system. Since the LCD module usually uses a general storage medium (such as Flash or EEPROM) to store the encryption key, attackers can directly extract the key information through hardware attack means such as physical detection and voltage glitch injection. Especially in open usage scenarios such as financial terminals, the physical contact risk faced by the device is significantly increased. When the attacker disassembles the device, they can easily obtain the statically stored key by using an electron microscope to observe the storage unit or through a bus sniffing tool. This key exposure risk directly threatens the reliability of the entire encryption mechanism. Once the key is stolen, the attacker can forge legitimate communication data or decrypt sensitive information. Therefore, in this application, the AES128 fixed key is burned through the LCD board and stored in the tamper-proof area of the security chip. That is, the tamper-proof area of the security chip has special physical protection and security mechanisms. It can effectively resist physical attacks, such as preventing attackers from obtaining the information stored therein through detection, disassembly, etc. At the same time, the tamper-proof area also has the function of self-destruction or encrypting data. When an abnormal physical access is detected, it will automatically take protective measures to ensure the security of the key.

[0021] In the above-mentioned LCD security protection system 100 based on encryption processing, the encryption initial vector acquisition module 120 is used to obtain the dynamic encryption initial vector through the controller. Among them, the encryption initial vector acquisition module 120 is used to: send the first encryption handshake command to the LCD board through the controller; return the initial vector of a predetermined number of bytes through the LCD board and reorganize the initial vector of the predetermined number of bytes to obtain the dynamic encryption initial vector; store the dynamic encryption initial vector in the circular buffer through the controller, and the security chip records the validity period of the dynamic encryption initial vector as 30 seconds.

[0022] Specifically, send the first encryption handshake command to the LCD board through the controller. It should be understood that in the entire LCD security protection system based on encryption processing, a trusted security channel needs to be established between the controller and the LCD board. The first encryption handshake is to negotiate and synchronize the encryption parameters (such as the dynamic encryption initial vector) required for subsequent communication between the two parties, so as to ensure the security of subsequent data transmission. That is, through the first encryption handshake, the controller can trigger the LCD board to generate the dynamic encryption initial vector, avoiding the problem of the predictable dynamic encryption initial vector, thereby enhancing the security of the encryption system.

[0023] Specifically, the LCD panel returns an initial vector of a predetermined number of bytes, and the initial vector of the predetermined number of bytes is recombined to obtain the dynamic encryption initial vector. It should be understood that in traditional security solutions, the generation of the initial vector often relies on the unilateral logical operations of the controller. This centralized generation mode has an inherent defect of insufficient entropy value. Even if a random number generator is used, an attacker can still analyze the periodic pattern of the random number generation algorithm or the characteristics of hardware noise by long-term monitoring of communication data packets. For example, for some pseudo-random number generators based on clock signals, there are predictable statistical biases in their output sequences within a specific time window. This hidden regularity enables the attacker to establish an initial vector prediction model through machine learning algorithms and gradually crack the dynamic elements of the encryption system. By returning an initial vector of a predetermined number of bytes through the LCD panel and recombining the initial vector, the present application can generate a high-quality dynamic encryption initial vector. It is worth mentioning that the present application sends a 0x05 command through the controller. After receiving the command, the backlight panel returns a 16-byte initial vector (such as 0x0011...FF) and recombines it in a specific byte order (big endian). In this way, refreshing the encryption vector before each heartbeat can avoid pattern recognition attacks caused by repeated use of the same encryption vector.

[0024] Specifically, the dynamic encryption initial vector is stored in a circular buffer through the controller, and the security chip records that the validity period of the dynamic encryption initial vector is 30 seconds. It should be understood that the dynamic encryption initial vector is stored in a circular buffer through the controller. That is, a circular buffer is a special data structure that has the characteristic of recycling memory space. During the operation of the system, the encryption operation may frequently use the dynamic encryption initial vector. Storing it in a circular buffer can improve the storage and access efficiency of data and reduce system overhead without frequent memory allocation and release operations. The security chip records that the validity period of the dynamic encryption initial vector is 30 seconds to prevent security risks brought by long-term use of the dynamic encryption initial vector. If an initial vector is used for a long time, an attacker may have more time and opportunities to analyze and crack it. By setting a shorter validity period, the initial vector can be invalidated after a certain time, forcing the system to re-obtain a new dynamic encryption initial vector, increasing the randomness and security of encryption.

[0025] Figure 2 It is a block diagram of the heartbeat data encryption module of the LCD security protection system based on encryption processing according to an embodiment of the present application. As Figure 2As shown, in the embodiment of the present application, the heartbeat data encryption module 130 is used to generate heartbeat data through the controller and perform composite encryption on the heartbeat data to obtain ciphertext. Among them, the heartbeat data encryption module 130 includes: a first page generation unit 131 of heartbeat data, which is used to generate the first page of the heartbeat data; a second page generation unit 132 of heartbeat data, which is used to generate the second page of the heartbeat data; and a ciphertext generation unit 133, which is used to perform composite encryption on the heartbeat data based on the fixed key and the dynamic encryption initialization vector to obtain the ciphertext.

[0026] Specifically, the first page generation unit 131 of the heartbeat data is used to generate the first page of the heartbeat data; the second page generation unit 132 of the heartbeat data is used to generate the second page of the heartbeat data. More specifically, in the embodiment of the present application, the first page includes a first fixed identifier, a first true random number, and a first checksum, and the second page includes a second fixed identifier, a second true random number, and a second checksum, wherein the first fixed identifier and the second fixed identifier have different byte counts. It should be understood that the heartbeat data is split into the first page and the second page, and each page contains different key information, such as fixed identifiers, true random numbers, and checksums, forming a multi-level data structure. This design makes it difficult for attackers to obtain complete and valid information by analyzing a single page, increasing the difficulty of data cracking. For example, even if an attacker obtains the first page of data, they cannot fully restore or tamper with the heartbeat data due to the lack of relevant information on the second page. In particular, the first true random number and the second true random number are included in the two pages respectively, further enhancing the randomness of the heartbeat data. Random numbers play a role in confusing and disturbing data during the encryption process, making each generated heartbeat data unique, effectively preventing replay attacks and statistical analysis attacks. It is worth mentioning that in a specific embodiment of the present application, the heartbeat data is divided into a two-page structure (16 + 13 bytes), with true random numbers and cumulative checksums embedded respectively, enhancing the anti-replay attack ability through dynamic paging and dual random numbers. Among them, the first page of the heartbeat data combines a fixed string (ZXHeartBeat) with a true random number and a checksum to ensure the legitimacy of the data source. The second page of the heartbeat data uses multiple segments of true random numbers to increase the entropy value and improve the cracking difficulty. Specifically, in the first page of the heartbeat data (16 bytes), it includes 11 bytes of fixed identifier, 4 bytes of true random number, and 1 byte of checksum. Among them, the 11-byte fixed identifier ("ZXHeartBeat") is used to identify the legitimate data source. The 4-byte true random number is used to prevent replay attacks. The 1-byte checksum (accumulation of the first 15 bytes) is used to quickly verify the data integrity. In the second page of the heartbeat data (13 bytes), it includes 8 bytes + 4 bytes of true random number and 1 byte of checksum. Among them, the 8 bytes + 4 bytes of true random number are used to increase the randomness complexity. The 1-byte checksum (accumulation of the first 12 bytes) is used for independent paging verification, avoiding the overhead of full-scale calculation.

[0027] Specifically, the ciphertext generation unit 133 is configured to perform composite encryption on the heartbeat data based on the fixed key and the dynamic encryption initialization vector to obtain the ciphertext. It should be understood that traditional security solutions mostly use a single encryption algorithm to protect display data, suffering from systematic defects such as easy leakage of static keys, predictability of initialization vectors, and weak anti-replay attack capabilities. The composite encryption method based on a fixed key and a dynamic encryption initialization vector can combine the advantages of both to make up for the deficiencies of single encryption. The fixed key provides the basic security of encryption, while the dynamic encryption initialization vector increases the randomness and unpredictability of encryption, thereby enhancing the overall security of encryption.

[0028] Embodiment 1: In a specific embodiment of the present application, the ciphertext generation unit 133 is used to: perform composite encryption on the heartbeat data using the AES128-CBC mode with the fixed key and the dynamic encryption initialization vector to obtain the ciphertext. It should be understood that AES (Advanced Encryption Standard) is a symmetric encryption algorithm that is widely used and considered secure and reliable at present. AES128 uses a key length of 128 bits. Under the current computing power, the time and resources required to brute-force crack this algorithm are extremely huge, and it can effectively resist most known attack methods, providing a solid security guarantee for the heartbeat data. The CBC (Cipher Block Chaining) mode is a working mode of the AES algorithm. It performs an exclusive OR operation on the ciphertext of the previous encrypted block and the current plaintext block before encryption. This chaining feature makes each ciphertext block depend on all the previous plaintext blocks and encryption operations. Even if the same plaintext appears at different positions, the encrypted ciphertext will be different, greatly increasing the randomness and security of encryption and effectively resisting statistical analysis attacks. Therefore, through the composite encryption of the AES128-CBC mode, the heartbeat data is converted into ciphertext form. During data transmission and storage, even if the data is intercepted, without the correct fixed key and dynamic encryption initialization vector, the attacker cannot decrypt the original heartbeat data, thus ensuring that the sensitive information contained in the heartbeat data is not leaked. In this way, for the ciphertext obtained through composite encryption, during transmission and storage, even if the data is intercepted, without the correct fixed key and dynamic encryption initialization vector, the attacker cannot easily decrypt the original heartbeat data. This ensures that the sensitive information contained in the heartbeat data is not leaked, protecting the privacy and security of the system. Specifically, in a specific embodiment of the present application, before AES128-CBC encryption, zero-padding supplementation and cumulative sum verification (independently calculated for each page) are adopted, taking into account both data integrity and encryption efficiency to prevent tampering and transmission errors. Then, using the AES128-CBC mode, with a fixed key (such as "0123456789ABCDEF") and a dynamic encryption initialization vector, 29 bytes of original data are encrypted to generate 32 bytes of ciphertext (padded with zeros to a multiple of the block size). Among them, the ciphertext is sent through the 0x06 command. After the backlight board decrypts it, it verifies the random number and the cumulative sum and returns a 0x86 response (success / failure). Then, the dynamic encryption initialization vector is requested in real time through an independent command (0x05) and stored separately from the fixed key, forming a dual-factor authentication system of dynamic + static to avoid system risks caused by the leakage of a single key. It is worth mentioning that the present application combines the heartbeat interval (1 minute) with the timeout black screen policy (2 minutes), binds the encryption communication mechanism to the device state, and realizes the execution of dynamic security policies. The timeout black screen policy means that the screen is forced to go black if there is no heartbeat within 2 minutes. This, combined with encryption verification, achieves double protection. True random number generation uses a hardware-level random source to ensure that the attacker cannot predict the random number sequence.

[0029] More specifically, in the AES128-CBC mode encryption process, each data block (here referring to heartbeat data) will perform an exclusive OR (XOR) operation with the ciphertext of the previous data block before encryption. For the first data block, it will perform an XOR operation with the dynamic encryption initialization vector. The purpose of this design is to disrupt the original data pattern, increase the complexity of encryption and the randomness of the ciphertext, so that even the same data block will produce different ciphertext outputs, effectively preventing statistical analysis attacks. Then, the data block after XOR processing is sent into the AES algorithm for encryption processing, using a fixed key as the encryption key. This entire process is repeatedly applied to each page of the heartbeat data until all pages are converted into ciphertext form. The finally obtained ciphertext not only contains all the information of the original heartbeat data, but also, due to the combined effects of the fixed key and the dynamic encryption initialization vector, greatly enhances the confidentiality and security of the data, ensuring that even if the data is intercepted during transmission, an unauthorized third party will be difficult to decrypt the original content. This composite encryption method makes full use of the powerful encryption capabilities of the AES algorithm and the chained encryption characteristics of the CBC mode to construct an efficient and secure data encryption solution.

[0030] Embodiment 2: It should be understood that traditional encryption mechanisms still have architectural flaws when dealing with advanced persistent threats. Although existing encryption schemes generally adopt an encryption mode that combines a dynamic encryption initialization vector and a fixed key, there is a hidden danger of insufficient coupling degree of elements in their linear encryption process - attackers can carry out dual attacks of key cracking and encryption initialization vector prediction in stages by separating and analyzing the action boundaries of the key and the initialization vector. For example, in a system using the standard AES-CBC mode, the fixed key and the dynamic encryption initialization vector are only associated through a simple XOR operation. This shallow coupling relationship enables attackers to directly generate legitimate data packets using the known encryption initialization vector generation rule after obtaining the key through a side-channel attack, rendering the encryption protection ineffective. More seriously, the traditional encryption process lacks in-depth structured processing of the key and data, and the interaction between encryption elements is limited to simple superposition at the algorithm level. When attackers analyze a large amount of ciphertext through machine learning, they can gradually establish a correlation model between the key characteristics and the evolution law of the encryption initialization vector, and then deduce the core parameters of the encryption system through differential analysis. This systematic vulnerability is particularly fatal in the man-in-the-middle attack scenario. Attackers only need to crack a single encryption element to carry out a chained attack, severely diluting the security gain of the multi-layer encryption mechanism.

[0031] Figure 3 It is a block diagram of the ciphertext generation unit in the LCD security protection system based on encryption processing according to an embodiment of the present application. As Figure 3As shown, in the embodiment of the present application, the ciphertext generation unit 133 includes: a fixed key structured mapping subunit 1331 for performing structured mapping encoding on the fixed key to obtain a fixed key structured mapping encoding vector; a heartbeat data structured mapping subunit 1332 for performing structured mapping encoding on the heartbeat data to obtain a heartbeat data structured mapping encoding vector; a primary encryption subunit 1333 for performing primary encryption based on sparse constraints on the heartbeat data structured mapping encoding vector based on the fixed key structured mapping encoding vector to obtain a fixed key-heartbeat data interaction encoding vector as the primary ciphertext; and a secondary encryption subunit 1334 for performing secondary encryption based on sparse constraints on the dynamic encryption initial vector and the primary ciphertext to obtain a secondary encryption interaction encoding vector as the ciphertext.

[0032] Based on this, in the process of using the AES128-CBC mode to perform composite encryption on the heartbeat data with the fixed key and the dynamic encryption initial vector to obtain the ciphertext, the technical concept of the present application is to reconstruct the interaction logic of the encryption elements through structured mapping encoding and a dual encryption architecture. During the encryption process, first, a non-linear feature transformation is performed on the fixed key to map it into a high-dimensional structured encoding vector, and at the same time, the heartbeat data is transformed into a multi-dimensional feature space representation through heterogeneous encoding rules. In the first encryption stage, the fixed key encoding vector and the data encoding vector perform feature cross-fusion in the implicit sparse constraint space to form an intermediate ciphertext with anti-statistical analysis characteristics. In the second encryption stage, a time-sensitive encoding vector of the dynamic encryption initial vector is introduced, and the intermediate ciphertext is dynamically perturbed and encrypted through spatial dimension recombination to finally generate a composite ciphertext with dual dynamic characteristics of time and space. This solution effectively blocks the separability of the key and the encryption initial vector, preventing attackers from carrying out effective attacks by isolatedly cracking any element. At the same time, the irreversibility of the structured encoding is used to destroy the correlation of the training data of the machine learning model, significantly enhancing the defense capabilities against side-channel attacks and differential analysis.

[0033] Specifically, the fixed key structured mapping subunit 1331 is used to perform structured mapping encoding on the fixed key to obtain a fixed key structured mapping encoding vector. Among them, the fixed key structured mapping subunit 1331 is used to: perform structured mapping encoding on the fixed key based on a fully connected layer to obtain the fixed key structured mapping encoding vector. It should be understood that considering the critical security vulnerability in the linear usage pattern of the fixed key. Since the key directly participates in the encryption operation without undergoing morphological transformation, after the attacker obtains the key fragment through side-channel attack, the complete key can be reverse-derived based on the algorithm logic. Therefore, in order to transform and hide the original features of the fixed key, disrupt its original structure and features, and make it difficult for the attacker to analyze the key features and rules from the ciphertext, the present application performs structured mapping encoding on the fixed key to obtain a fixed key structured mapping encoding vector. The fixed key structured mapping encoding vector obtained through structured mapping encoding can be more closely combined with other encryption elements in the subsequent encryption process to form a more complex encryption logic. This greatly increases the difficulty for the attacker to crack the encryption system. Even if the attacker obtains some encryption information, it is difficult to restore the original fixed key and other sensitive information through analysis, thereby enhancing the security of the entire encryption system. In particular, in a specific example of the present application, structured mapping encoding on the fixed key based on a fully connected layer is performed to obtain the fixed key structured mapping encoding vector. Specifically, in the structured encoding stage, the fixed key is input into the feature space transformation engine constructed by a multi-level fully connected network. Through the alternating action of the linear combination of the weight matrix and the non-linear activation function, the original key bit sequence is mapped to a high-dimensional continuous space. During this process, each key bit establishes a weighted connection with all neurons in the fully connected layer. Through the non-linear transformation of the activation function (such as ReLU or Sigmoid), the discrete bit features of the original key are reconstructed into a distributed representation with complex correlations.

[0034] Specifically, the heartbeat data structured mapping subunit 1332 is configured to perform structured mapping encoding on the heartbeat data to obtain a heartbeat data structured mapping encoded vector. Among them, the heartbeat data structured mapping subunit 1332 is configured to: perform the structured mapping encoding based on the fully connected layer on the heartbeat data to obtain the heartbeat data structured mapping encoded vector. It should be understood that considering that the heartbeat data contains an identification field with a fixed format and a periodically updated check value, its plaintext structure may still retain specific statistical characteristics after encryption. For example, in the standard encryption process, the repeated occurrence of fixed identification bits will form a regular distribution of ciphertext blocks. This structural residue enables attackers to locate key data segments through ciphertext clustering analysis, and then implement selective tampering or replay attacks. Based on this, in the technical solution of this application, the heartbeat data is subjected to structured mapping encoding to reconstruct the existence form of the data, and a heartbeat data structured mapping encoded vector is obtained. In particular, in a specific example of this application, the structured mapping encoding based on the fully connected layer is performed on the heartbeat data to obtain the heartbeat data structured mapping encoded vector. Specifically, in the preprocessing stage, the heartbeat data is input into an encoding engine composed of a multi-layer fully connected network. Through the linear combination of the weight matrix and the non-linear transformation of the activation function (such as Sigmoid or Tanh), the original byte sequence is mapped to an implicit high-dimensional feature space. For example, after the fixed identifier in the first page of data is processed by the fully connected layer, its bit pattern is decomposed into a weighted combination of multiple orthogonal basis vectors, and the true random number has a non-linear interaction with the network weights, generating a distribution feature with chaotic characteristics. This encoding process not only changes the physical storage form of the data, but also reconstructs the association rules between data elements at the mathematical level, so that the same plaintext data presents a completely heterogeneous feature space distribution in different encryption sessions.

[0035] Figure 4 Block diagram of a primary encryption subunit in an LCD security protection system based on encryption processing according to an embodiment of the present application. As Figure 4As shown, in the embodiment of the present application, the primary encryption subunit 1333 is configured to perform primary encryption based on sparse constraints on the heartbeat data structured mapping encoding vector by using the fixed key structured mapping encoding vector to obtain a fixed key-heartbeat data interactive encoding vector as the primary ciphertext. Among them, the primary encryption subunit 1333 includes: a one-dimensional convolutional feature phase space reconstruction secondary subunit 1333-1, configured to perform one-dimensional convolutional feature phase space reconstruction on the fixed key structured mapping encoding vector and the heartbeat data structured mapping encoding vector to obtain a set of fixed key local structured mapping encoding vectors and a set of heartbeat data local structured mapping encoding vectors; a fixed key-heartbeat data implicit interaction association secondary subunit 1333-2, configured to calculate an implicit interaction association matrix between each pair of corresponding fixed key local structured mapping encoding vectors and heartbeat data local structured mapping encoding vectors in the set of fixed key local structured mapping encoding vectors and the set of heartbeat data local structured mapping encoding vectors to obtain a set of fixed key-heartbeat data implicit interaction association matrices; a spatial sparse constraint weighted aggregation secondary subunit 1333-3, configured to perform an aggregation process based on a spatial sparse constraint factor weighting on the set of fixed key-heartbeat data implicit interaction association matrices to obtain the fixed key-heartbeat data interactive encoding vector. It should be understood that considering that there are fatal linear coupling defects in the interaction mode between the key and the data. When the fixed key directly participates in the encryption operation in its original form, the explicit correlation between its bit sequence and the algorithm logic provides an opportunity for side-channel attacks. By monitoring the interaction characteristics between the key bits and the algorithm round function during the encryption process, the attacker can gradually restore the key structure. More seriously, the simple XOR or linear transformation operation between the key and the data makes the interaction relationship between the encryption elements separable - after the attacker cracks the key, they can deduce the data encryption path through reverse engineering, and then forge legitimate data packets. This linear interaction mode is particularly vulnerable to adversarial machine learning analysis. The attacker can establish a correlation model between the key characteristics and the ciphertext form by training a deep neural network, and finally realize the reverse derivation of the encryption logic. Therefore, in the present application, primary encryption based on sparse constraints is performed on the heartbeat data structured mapping encoding vector by using the fixed key structured mapping encoding vector to obtain a fixed key-heartbeat data interactive encoding vector as the primary ciphertext. That is, the fixed key-heartbeat data interactive encoding vector obtained through primary encryption is used as the primary ciphertext, which integrates the characteristics of the fixed key and the heartbeat data and has undergone complex interaction processing. This makes it almost impossible for the attacker to restore the original fixed key and heartbeat data from the primary ciphertext without the correct decryption method and key, thus greatly improving the encryption security and protecting the confidentiality of sensitive information in the system.

[0036] Specifically, the one-dimensional convolutional feature phase space reconstruction secondary subunit 1333-1 is used to perform one-dimensional convolutional feature phase space reconstruction on the fixed key structured mapping encoded vector and the heartbeat data structured mapping encoded vector to obtain a set of fixed key local structured mapping encoded vectors and a set of heartbeat data local structured mapping encoded vectors, which is represented by the one-dimensional convolutional feature phase space reconstruction formula as follows: ; where is the fixed key structured mapping encoded vector, is the heartbeat data structured mapping encoded vector, is for performing one-dimensional convolutional feature phase space reconstruction, and are respectively the 1st, 2nd, th, and th fixed key local structured mapping encoded vectors in the set of fixed key local structured mapping encoded vectors, is the set of fixed key local structured mapping encoded vectors, and are respectively the 1st, 2nd, th, and th heartbeat data local structured mapping encoded vectors in the set of heartbeat data local structured mapping encoded vectors, is the set of heartbeat data local structured mapping encoded vectors, and and The lengths are the same. It should be understood that traditional encryption schemes often have potential security flaws when dealing with the feature interaction between fixed keys and heartbeat data, as they often ignore the local dependencies within the vectors. As static high-dimensional feature representations, the globally structured mapping encoding vectors of fixed keys and the globally structured mapping encoding vectors of heartbeat data are difficult to directly reveal the implicit local structural correlations in their global feature distributions. Based on the phase space reconstruction principle of dynamic system theory, it is necessary to map the static feature vectors to an abstract feature space with potential spatio-temporal correlations through a delay embedding mechanism that simulates dynamic trajectories. One-dimensional convolution operations can effectively mine the latent dimensional correlations and pattern regularities within the feature vectors through local perception and non-linear transformation in the form of a sliding window, thus solving the problems of single feature interaction patterns and insufficient anti-reverse analysis capabilities in traditional methods. Through the one-dimensional convolution feature phase space reconstruction technology, the high-dimensional global feature vectors of fixed key features and heartbeat data features can be decomposed into a set of multi-group locally structured mapping encoding vectors, namely, the set of fixed key locally structured mapping encoding vectors and the set of heartbeat data locally structured mapping encoding vectors. By introducing the weight learning mechanism of the convolution kernel and the non-linear mapping of the activation function, the original feature space is lifted to a more expressive implicit space. Each convolution kernel, as a feature detector for a specific pattern, captures the local structural information within the vector from different perspectives, generating a set of locally feature representations with multi-modal characteristics. This process not only enhances the modeling ability of the local dependencies within the features, but also constructs feature redundancy through distributed representations, forming a robust feature system that resists noise interference and local tampering, providing an input basis with non-linear separability for subsequent encryption interactions. In this way, the global feature vectors of fixed key features and heartbeat data features are reconstructed into a feature set containing multi-scale local structural information, namely, the set of fixed key locally structured mapping encoding vectors and the set of heartbeat data locally structured mapping encoding vectors. Each locally structured mapping encoded feature corresponds to an abstract pattern feature perceived by a specific convolution kernel, breaking the linear separability of the original features through non-linear transformation. The set of multi-perspective representations generated by the parallel operation of multiple convolution kernels forms a distributed coding system that covers different granularity feature interaction patterns. The feature redundancy mechanism effectively improves the tolerance of the model to noisy data and partial feature tampering, while the explicit modeling of local structures strengthens the non-linear coupling relationship between encryption elements. This reconstruction process makes it difficult for attackers to restore the original feature distribution law through statistical analysis or reverse engineering, significantly enhancing the encryption system's ability to resist side-channel attacks and pattern recognition cracking.

[0037] Specifically, the fixed key-heartbeat data implicit interaction correlation secondary subunit 1333-2 is used to calculate the implicit interaction correlation matrix between each corresponding fixed key local structured mapping coding vector and heartbeat data local structured mapping coding vector in the set of fixed key local structured mapping coding vectors and the set of heartbeat data local structured mapping coding vectors to obtain a set of fixed key-heartbeat data implicit interaction correlation matrices, which is represented by the fixed key-heartbeat data implicit interaction correlation formula as follows: ; where represents the transpose operation, and respectively represent and the corresponding weight matrices, represents matrix multiplication, is and the length of the vector after multiplication, is and The fixed key-heartbeat data implicit interaction correlation matrix between them. It should be understood that although the set of fixed key local structured mapping coding vectors and the set of the heartbeat data local structured mapping coding vectors contain multi-perspective local features, the potential correlation between their dimensions is still implicit in the linear or shallow non-linear space. To break through the limitations of the predefined interaction space, it is necessary to construct a dynamic implicit query space through a data-driven approach, and map the interaction relationship between feature pairs to a high-dimensional implicit association domain. By introducing an implicit query mechanism based on model parameter coding, the deep non-linear interaction relationship between the fixed key features and the local features of the heartbeat data can be dynamically captured, thereby eliminating the prior constraints of manually defined interaction rules and solving the core problems of single feature interaction pattern, poor interpretability, and weak anti-reverse engineering ability in traditional methods. Specifically, by projecting each group of feature pairs into the implicit association domain and using the linear combination and non-linear transformation of the weight matrix, a set of fixed key-heartbeat data implicit interaction correlation matrices representing the multi-dimensional interaction intensity between the two is generated. Each fixed key-heartbeat data implicit interaction correlation matrix, as a mathematical abstraction of cross-modal feature association, not only quantifies the coupling strength between local feature dimensions, but also reconstructs the mathematical expression form of the interaction logic through the distributed coding mechanism of the implicit space. This process breaks through the expression ability limitation of the explicit interaction function, establishes an association bridge with anti-reverse parsing characteristics between feature pairs, and provides an intermediate representation with inseparability and non-linear separability for the deep integration of subsequent encryption elements. Here, each fixed key-heartbeat data implicit interaction correlation matrix, through the non-linear mapping in the implicit query space, elevates the linear correlation relationship of the original feature pairs to a high-dimensional abstract association domain, forming interaction features with anti-pattern recognition attack characteristics. The dynamic generation mechanism of the implicit space makes it impossible for attackers to reverse-derive the interaction logic through a fixed algorithm, and the multi-dimensional association characteristics of the elements in the matrix effectively cover the action path of a single feature dimension. As an intermediate carrier for the deep coupling of encryption elements, this set not only retains the fine-grained interaction information of local features, but also destroys the separability of keys and data in the traditional encryption process through implicit coding, significantly enhancing the ability of the encryption system to resist side-channel attacks and differential analysis, and laying a core data foundation for constructing a multi-layer dynamic encryption mechanism.

[0038] Specifically, the spatial sparse constraint weighted aggregation secondary subunit 1333-3 is used to perform weighted aggregation processing on the set of fixed key-heartbeat data implicit interaction correlation matrices based on a spatial sparse constraint factor to obtain the fixed key-heartbeat data interaction coding vector. Among them, the spatial sparse constraint weighted aggregation secondary subunit 1333-3 is used to: perform microdifferential manifold structural optimization on each fixed key-heartbeat data implicit interaction correlation matrix in the set of fixed key-heartbeat data implicit interaction correlation matrices to obtain a set of optimized fixed key-heartbeat data implicit interaction correlation matrices; calculate the square of the Frobenius norm of each optimized fixed key-heartbeat data implicit interaction correlation matrix in the set of optimized fixed key-heartbeat data implicit interaction correlation matrices to obtain a set of fixed key-heartbeat data implicit interaction spatial constraint factors; perform normalization processing on the set of fixed key-heartbeat data implicit interaction spatial constraint factors based on the softmax function to obtain a set of fixed key-heartbeat data implicit interaction spatial sparse constraint factors; based on the set of fixed key-heartbeat data implicit interaction spatial sparse constraint factors, perform weighted aggregation on the set of optimized fixed key-heartbeat data implicit interaction correlation matrices to obtain the fixed key-heartbeat data interaction coding vector.

[0039] Specifically, performing microdifferential manifold structural optimization on each fixed key-heartbeat data implicit interaction correlation matrix in the set of fixed key-heartbeat data implicit interaction correlation matrices to obtain a set of optimized fixed key-heartbeat data implicit interaction correlation matrices, which is expressed by the microdifferential manifold structural optimization formula as: ; where is the th eigenvalue in is the th eigenvalue in is the exponential function value with the natural constant as the base, is and the relative phase of the fixed key-heartbeat data implicit interaction correlation between them, is each eigenvalue in the fixed key-heartbeat data implicit interaction correlation phase covariance matrix, is and the fixed key-heartbeat data implicit interaction correlation phase covariance matrix between them, is 's inverse matrix, is Optimized Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrix. It should be understood that although the set of Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrices contains multi - dimensional interaction relationships, its original non - linear correlation pattern has non - integrability and local coordinate dependence at the global geometric level, resulting in dynamic instability in the encryption element coupling mechanism. To eliminate the local topological distortion effect in the non - linear manifold space, it is necessary to establish an affine connection framework through differential geometry theory, map the Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrix to a canonical space with a flat connection structure, and solve the core defects of uncontrollable feature interaction paths and weakened anti - reverse analysis ability caused by manifold curvature differences in traditional methods. Through the micro - differential manifold structure optimization technology, it is possible to reconstruct the geometric topological characteristics of the Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrix and realize the normalized expression of the feature interaction dynamics model in the flat connection space. Specifically, based on the affine transformation mechanism of the Fixed Key - Heartbeat Data Implicit Interaction Phase Covariance Matrix the locally structured mapping coding vectors of the feature pairs to the fixed key after phase - space reconstruction and the locally structured mapping coding vectors of the heartbeat data The local non - linear correlation pattern is converted into a globally integrable micro - differential manifold structure, eliminating the covariant differential distortion caused by coordinate transformation. By constructing an interaction optimization system for the Fixed Key - Heartbeat Data Implicit Interaction Phase Covariance Matrix and its inverse matrix while maintaining the invariance of feature interaction morphism transfer, redundant high - order non - linear interactions are stripped, and a manifold dynamics mapping model with the minimum computational complexity is established to ensure that the encryption element interaction logic satisfies the Lie group symmetry constraint and the connection parallel transport consistency at the differential geometry level. In this way, the set of Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrices is optimized into a micro - differential manifold representation system with a flat connection structure. The introduction of the phase covariance matrix makes the feature interaction path maintain covariant differential invariance in the local affine coordinates, eliminating the interference of non - linear manifold curvature on the encryption element coupling mechanism. The set of Optimized Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrices compresses the original high - dimensional non - linear interaction pattern into a low - dimensional resolvable geometric topological structure through a normalized connection space mapping, significantly reducing the computational redundancy of feature interaction modeling.

[0040] Specifically, calculate the square of the Frobenius norm of each Optimized Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrix in the set of Optimized Fixed Key - Heartbeat Data Implicit Interaction Correlation Matrices to obtain the set of Fixed Key - Heartbeat Data Implicit Interaction Space Constraint Factors, which is expressed by the Fixed Key - Heartbeat Data Implicit Interaction Space Constraint Factor calculation formula as: ; where is to calculate the square of the Frobenius norm of the matrix is The corresponding fixed key - heartbeat data implicit interaction space constraint factor. It should be understood that the calculation of the square of the Frobenius norm can transform the numerical distribution characteristics of the optimized fixed key - heartbeat data implicit interaction correlation matrix into a set of quantifiable and comparable fixed key - heartbeat data implicit interaction space constraint factors. Based on the global energy accumulation characteristics of matrix elements, the norm square value directly represents the order of magnitude and distribution density of significant interaction elements in the matrix, providing a mathematical benchmark for the objective quantification of sparsity strength. This process eliminates the interference of matrix dimension and local noise through a standardized measurement method, establishes a sparsity evaluation system centered on energy density, and provides a set of constraint factors with numerical comparability and mathematical analyzability for subsequent weight normalization and adaptive aggregation.

[0041] Specifically, perform normalization processing based on the softmax function on the set of the fixed key - heartbeat data implicit interaction space constraint factors to obtain a set of fixed key - heartbeat data implicit interaction space sparse constraint factors, which is expressed by the fixed key - heartbeat data normalization formula as: ; where is function, is The corresponding fixed key-heartbeat data implicit interaction space sparse constraint factor. It should be understood that although the set of fixed key-heartbeat data implicit interaction space constraint factors quantifies the sparsity degree of the optimized correlation matrix through norm calculation, the absolute value distribution ranges are inconsistent, and directly used for aggregation is likely to cause problems such as high-sparsity matrices being weakened by low weights or low-sparsity noises being mis-enhanced. To establish a unified probabilistic weight assignment standard and strengthen the guiding role of the sparsity prior assumption in the encryption element interaction logic, it is necessary to map the set of constraint factors to a normalized probability space through the softmax function, to solve the defect that the static weight assignment mechanism in traditional methods cannot dynamically adapt to the importance of feature interaction patterns. By transforming the fixed key-heartbeat data implicit interaction space constraint factors into a set of fixed key-heartbeat data implicit interaction space sparse constraint factors that conform to the probability distribution characteristics, an adaptive weight assignment mechanism based on sparsity intensity can be constructed. Specifically, through the exponential transformation and normalization operation of the softmax function, the absolute sparsity measure of the original fixed key-heartbeat data implicit interaction space constraint factors is converted into relative probability weights, so that the high-sparsity optimized fixed key-heartbeat data implicit interaction correlation matrix dominates in the aggregation process, and the contribution degree of the low-sparsity optimized fixed key-heartbeat data implicit interaction correlation matrix is exponentially compressed. This process eliminates the interference of scale differences on weight assignment through probability space mapping, and at the same time enforces the constraint condition that the sum of weights is 1, ensuring that the fusion process of encryption element interaction information not only focuses on key feature correlation patterns but also conforms to mathematical norms, providing a dynamic weight benchmark with noise resistance and interpretability for subsequent weighted aggregation. In this way, the probability characteristics of the normalized weights enhance the interpretability of the model for feature interaction patterns, and the distribution visualization of the fixed key-heartbeat data implicit interaction space sparse constraint factors can clearly reveal the core correlation dimensions between encryption elements.

[0042] Specifically, based on the set of fixed key-heartbeat data implicit interaction space sparse constraint factors, weighted aggregation is performed on the set of optimized fixed key-heartbeat data implicit interaction correlation matrices to obtain the fixed key-heartbeat data interaction coding vector, which is expressed by the fixed key-heartbeat data weighted aggregation formula as: ; where is the fixed key-heartbeat data interaction coding matrix, is the shape reshaping, It is a fixed key - heartbeat data interaction coding vector. It should be understood that although the set of optimized fixed key - heartbeat data implicit interaction correlation matrices improves the representation quality of local interaction patterns through manifold optimization and sparse constraints, its heterogeneous distribution characteristics make it difficult to effectively distinguish high - value encryption elements from low - efficiency noise signals by direct arithmetic mean or simple splicing. To break through the limitations of traditional aggregation methods in measuring the value of feature interaction information, it is necessary to introduce a dynamic weighting mechanism based on the sparse constraint factor of the fixed - key - heartbeat data implicit interaction space, using the sparsity intensity of the matrix as the information value quantization standard to solve the core problems of weakened encryption element interaction logic and insufficient anti - attack ability caused by fixed weight allocation. Through the sparsity - driven adaptive weighted aggregation technology, it is possible to achieve the information value screening and deep fusion of the set of optimized fixed key - heartbeat data implicit interaction correlation matrices. Specifically, based on the dynamic weight allocation of the set of sparse constraint factors of the fixed - key - heartbeat data implicit interaction space, the sparsity intensity of each optimized fixed key - heartbeat data implicit interaction correlation matrix is mapped to its contribution weight in the aggregation process, so that the core encryption element interaction pattern represented by the high - sparsity matrix dominates the generation of the final feature coding vector. This process constructs a hierarchical fusion mechanism for encryption element interaction information through the positive correlation between weight and sparsity, suppressing the interference of low - efficiency or redundant interaction noise on the encryption logic, ensuring that the aggregation result precisely focuses on the key feature interaction paths with anti - reverse parsing characteristics, and providing a high - purity and strong - robustness interaction coding basis for constructing a multi - level dynamic encryption system. In this way, the dynamic weight allocation mechanism with sparse constraints destroys the separability of traditional encryption elements, significantly improves the defense ability of the encryption system against side - channel attacks and differential analysis, and at the same time provides a feature interaction map with mathematical consistency for the interpretability verification of the encryption logic. This step is not simply averaging or splicing multiple optimized fixed key - heartbeat data implicit interaction correlation matrices, but weighted fusion according to the sparse constraint factor of the fixed - key - heartbeat data implicit interaction space, and this weighted fusion is dynamically adaptive, and the weight size completely depends on the sparse constraint factor of the fixed - key - heartbeat data implicit interaction space of each optimized fixed key - heartbeat data implicit interaction correlation matrix.

[0043] Specifically, the secondary encryption subunit 1334 is configured to perform secondary encryption on the dynamic encryption initial vector and the primary ciphertext based on sparse constraints to obtain a secondary encrypted interactive coding vector as the ciphertext. It should be understood that considering that the interaction between the dynamic encryption initial vector and the intermediate ciphertext often adopts a linear superposition method, this shallow association enables attackers to gradually crack the encryption elements through separation and analysis techniques. Even if the primary encryption process has high security, if the secondary encryption stage still uses a simple operation mode (such as XOR or linear transformation), the attacker can still establish a prediction model by intercepting the correlation between the dynamic encryption initial vector and the secondary ciphertext. For example, in a standard multi-layer encryption system, if there is a fixed algorithm association between the secondary encryption key and the dynamic encryption initial vector, after the attacker cracks the generation rule of the dynamic encryption initial vector, they can reverse-derive the encryption logic, rendering the multi-layer protection mechanism ineffective. This systematic defect stems from the lack of a non-linear coupling and dynamic association blocking mechanism between the encryption elements. Therefore, in this application, secondary encryption based on sparse constraints is performed on the dynamic encryption initial vector and the primary ciphertext to obtain a secondary encrypted interactive coding vector as the ciphertext. In this way, the secondary encrypted interactive coding vector (i.e., the ciphertext) obtained through secondary encryption integrates the characteristics of the primary ciphertext and the dynamic encryption initial vector and undergoes complex feature interaction processing. This makes it almost impossible for attackers to restore the original heartbeat data and the fixed key from the ciphertext without the correct dynamic encryption initial vector and the corresponding decryption algorithm, greatly improving the security of encryption and protecting the confidentiality of sensitive information in the system. In particular, the dynamic nature of the dynamic encryption initial vector ensures that different initial vectors are used for each encryption. Even if the attacker intercepts the ciphertext and attempts a replay attack, since the dynamic encryption initial vector used by the receiving party has been updated, the replayed ciphertext cannot pass the decryption verification, effectively preventing replay attacks and ensuring the authenticity and effectiveness of data transmission.

[0044] In the above LCD security protection system 100 based on encryption processing, the decryption verification module 140 is used to decrypt and verify the ciphertext through the LCD panel after receiving the ciphertext to obtain a decryption result. It should be understood that during the data transmission process, the ciphertext may be intercepted, tampered with, or forged by an attacker. By decrypting and verifying the ciphertext, the LCD panel can determine whether the received ciphertext is encrypted from the original data sent by a legitimate sender, ensuring the authenticity of the data. Only the verified real data can be correctly processed and used by the system, avoiding system failures or security incidents caused by using false data. One of the main purposes of decryption verification is to recover the original heartbeat data from the ciphertext. The decryption verification step can effectively identify and resist various security threats, such as data tampering, forgery, and replay attacks. By strictly verifying the ciphertext, the system can timely detect abnormal data and take corresponding measures to prevent security vulnerabilities from being exploited, thereby enhancing the overall security of the system. Specifically, the LCD panel uses the AES128-CBC mode for decryption operations. This mode requires that each ciphertext block must be XORed with the output of the previous ciphertext block before decryption. For the first data block, it is directly XORed with the dynamic encryption initialization vector. This process effectively reverses the transformation in the encryption stage, enabling accurate recovery of the original information even if the same plaintext data generates different ciphertexts in different encryption sessions. During the decryption process, the system also verifies the checksum field in the heartbeat data, including but not limited to mechanisms such as cumulative sum check, to ensure that the data has not been tampered with. The checksum calculation covers all parts of the heartbeat data, such as fixed identifiers, true random numbers, etc., thus ensuring the integrity of the decrypted data. Once all data blocks have been successfully decrypted and verified without errors, the LCD panel can restore the original heartbeat data from the ciphertext and confirm its legality and accuracy.

[0045] In the above LCD security protection system 100 based on encryption processing, the execution action module 150 is used to determine the execution action based on the decryption result. It should be understood that in the LCD security protection system based on encryption processing, after decrypting and verifying the ciphertext, the obtained decryption result reflects whether the received data is true, complete, and legal. Determining the execution action according to the decryption result enables the system to respond to various situations in a timely manner and ensure the safe and stable operation of the system. For example, if the decryption result shows that the data has been tampered with, the system can take corresponding measures to prevent malicious attacks and ensure its own security. Specifically, if the decryption result indicates that the received data packet is a valid monitoring instruction or status update, the system may trigger corresponding alarm mechanisms, adjust the camera angle, or update the access permissions of the access control system, etc. On the other hand, if the decryption result reveals that the data is abnormal, such as detecting signs of tampering or failing to pass the checksum verification, the system will take a series of defensive measures to prevent potential security threats. These measures may include but are not limited to immediately terminating the current session, recording error logs for subsequent analysis, sending warning notifications to administrators, and automatically entering the security mode to restrict unauthorized access. For devices designed with a timeout black screen policy, once the number of decryption failures exceeds the preset threshold, the system may also force the screen to turn off as an additional protection measure to avoid the leakage of sensitive information. Determining the execution action based on the decryption result can not only ensure the normal operation of the system, but also effectively resist various forms of attack attempts and maintain the security and reliability of the entire system. Through the accurate judgment and timely response to the decryption result, this mechanism provides a solid security foundation for various key applications involving the LCD display module.

[0046] In summary, the LCD security protection system 100 based on encryption processing according to the embodiments of the present application is clarified. At the key management level, the AES128 fixed key is burned into the LCD board and stored in the tamper-proof area of the security chip. Then, through the handshake interaction between the controller and the LCD board, a dynamic encryption initialization vector with unpredictability and a validity period of 30 seconds is generated. And at the data encryption level, a paged heartbeat data structure design is adopted for data compound encryption to obtain the ciphertext. Then, the LCD board decrypts and verifies the ciphertext and determines the execution action. In this way, through the hardwareization of key storage, the dynamicization of the initialization vector, and the randomization of the data structure, an LCD communication protection system suitable for high-security scenarios with a multi-level dynamic encryption mechanism is constructed, improving the defects of easy leakage of static keys, predictability of the initialization vector, and weak anti-replay attack ability.

[0047] As described above, the LCD security protection system 100 based on encryption processing according to the embodiments of the present application can be implemented in various terminal devices. In one example, the LCD security protection system 100 based on encryption processing can be integrated into the terminal device as a software module and / or a hardware module. For example, the LCD security protection system 100 based on encryption processing can be a software module in the operating system of the terminal device, or can be an application program developed for the terminal device; of course, the LCD security protection system 100 based on encryption processing can also be one of the many hardware modules of the terminal device.

[0048] Alternatively, in another example, the LCD security protection system 100 based on encryption processing and the terminal device can also be separate devices, and the LCD security protection system 100 based on encryption processing can be connected to the terminal device through a wired and / or wireless network and transmit interaction information in accordance with a predefined data format.

Claims

1. An LCD security protection system based on encryption processing, characterized in that, Including: A key fixed storage module, which is used to burn the AES128 fixed key through an LCD board and store it in the tamper-proof area of the security chip; An encryption initial vector acquisition module, which is used to obtain a dynamic encryption initial vector through a controller; A heartbeat data encryption module, which is used to generate heartbeat data through the controller and perform composite encryption on the heartbeat data to obtain a ciphertext; A decryption verification module, which is used to decrypt and verify the ciphertext through the LCD board to obtain a decryption result after receiving the ciphertext; An execution action module, which is used to determine an execution action based on the decryption result.

2. The LCD security protection system based on encryption processing according to claim 1, characterized in that The encryption initial vector acquisition module is used for: sending a first encryption handshake command to the LCD board through the controller; returning an initial vector of a predetermined number of bytes through the LCD board, and reorganizing the initial vector of the predetermined number of bytes to obtain the dynamic encryption initial vector; storing the dynamic encryption initial vector in a circular buffer through the controller, and the security chip records the validity period of the dynamic encryption initial vector as 30 seconds.

3. The LCD security protection system based on encryption processing according to claim 2, characterized in that, The heartbeat data encryption module includes: a first page generation unit for the heartbeat data, which is used to generate the first page of the heartbeat data; a second page generation unit for the heartbeat data, which is used to generate the second page of the heartbeat data; a ciphertext generation unit, which is used to perform composite encryption on the heartbeat data based on the fixed key and the dynamic encryption initial vector to obtain the ciphertext.

4. The LCD security protection system based on encryption processing according to claim 3, characterized in that, The first page includes a first fixed identifier, a first true random number, and a first checksum, and the second page includes a second fixed identifier, a second true random number, and a second checksum, wherein the first fixed identifier and the second fixed identifier have different numbers of bytes.

5. The LCD security protection system based on encryption processing according to claim 4, characterized in that, The ciphertext generation unit is used for: performing composite encryption on the heartbeat data using the AES128-CBC mode with the fixed key and the dynamic encryption initial vector to obtain the ciphertext.

6. The LCD security protection system based on encryption processing according to claim 4, characterized in that, The ciphertext generation unit includes: a fixed key structured mapping subunit, which is used to perform structured mapping encoding on the fixed key to obtain a fixed key structured mapping encoding vector; a heartbeat data structured mapping subunit, which is used to perform structured mapping encoding on the heartbeat data to obtain a heartbeat data structured mapping encoding vector; a primary encryption subunit, which is used to perform primary encryption based on sparse constraints on the heartbeat data structured mapping encoding vector based on the fixed key structured mapping encoding vector to obtain a fixed key-heartbeat data interaction encoding vector as the primary ciphertext; a secondary encryption subunit, which is used to perform secondary encryption based on sparse constraints on the dynamic encryption initial vector and the primary ciphertext to obtain a secondary encryption interaction encoding vector as the ciphertext.

7. The LCD security protection system based on encryption processing according to claim 6, wherein The fixed key structured mapping subunit is used for: performing structured mapping encoding on the fixed key based on a fully connected layer to obtain the fixed key structured mapping encoding vector.

8. The LCD security protection system based on encryption processing according to claim 7, characterized in that, The heartbeat data structured mapping subunit is used for: performing the structured mapping encoding based on the fully connected layer on the heartbeat data to obtain the heartbeat data structured mapping encoding vector.

9. The LCD security protection system based on encryption processing according to claim 8, characterized in that, The primary encryption subunit includes: a one-dimensional convolutional feature phase space reconstruction secondary subunit, configured to perform one-dimensional convolutional feature phase space reconstruction on the fixed key structured mapping encoded vector and the heartbeat data structured mapping encoded vector to obtain a set of fixed key local structured mapping encoded vectors and a set of heartbeat data local structured mapping encoded vectors; a fixed key-heartbeat data implicit interaction correlation secondary subunit, configured to calculate an implicit interaction correlation matrix between each pair of corresponding fixed key local structured mapping encoded vectors and heartbeat data local structured mapping encoded vectors in the set of fixed key local structured mapping encoded vectors and the set of heartbeat data local structured mapping encoded vectors to obtain a set of fixed key-heartbeat data implicit interaction correlation matrices; and a spatial sparse constraint weighted aggregation secondary subunit, configured to perform an aggregation process weighted by a spatial sparse constraint factor on the set of fixed key-heartbeat data implicit interaction correlation matrices to obtain the fixed key-heartbeat data interaction encoded vector.

10. The LCD security protection system based on encryption processing according to claim 9, characterized in that, The spatial sparse constraint weighted aggregation secondary subunit is configured to: perform a micro-manifold structure optimization on each fixed key-heartbeat data implicit interaction correlation matrix in the set of fixed key-heartbeat data implicit interaction correlation matrices to obtain a set of optimized fixed key-heartbeat data implicit interaction correlation matrices; calculate the square of the Frobenius norm of each optimized fixed key-heartbeat data implicit interaction correlation matrix in the set of optimized fixed key-heartbeat data implicit interaction correlation matrices to obtain a set of fixed key-heartbeat data implicit interaction space constraint factors; perform a normalization process based on the softmax function on the set of fixed key-heartbeat data implicit interaction space constraint factors to obtain a set of fixed key-heartbeat data implicit interaction space sparse constraint factors; based on the set of fixed key-heartbeat data implicit interaction space sparse constraint factors, perform a weighted aggregation on the set of optimized fixed key-heartbeat data implicit interaction correlation matrices to obtain the fixed key-heartbeat data interaction encoded vector.

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