LCD security protection system based on encryption processing

Abstract

The present application provides an LCD security protection system based on encryption processing, which relates to the field of security protection. At the key management level, the AES128 fixed key is burned into the LCD panel and stored in the tamper-proof area of the security chip. Then, a dynamic encryption initialization vector with unpredictability and a validity period of 30 seconds is generated through handshake interaction between the controller and the LCD panel. At the data encryption level, a paged heartbeat data structure design is used to perform data composite encryption to obtain ciphertext. Then, the ciphertext is decrypted and verified by the LCD panel and the execution action is determined. 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 with a multi-level dynamic encryption mechanism that is adaptable to high-security scenarios is constructed, which improves the defects of easy leakage of static keys, predictable initialization vectors and weak anti-replay attack capabilities.

Description

Technical Field

[0001] The present application relates to the field of security protection, and more particularly, in an embodiment of the present application, relates to an LCD security protection system based on encryption processing. Background Art

[0002] With the widespread adoption of liquid crystal display (LCD) modules in key areas such as financial terminals, industrial control equipment, and intelligent security systems, the security of their data transmission channels has become increasingly prominent. In scenarios involving the exchange of sensitive information, LCD modules not only serve as the human-machine interface but also become a key target for attackers to conduct side-channel attacks, data tampering, and counterfeit communications.

[0003] Traditional security solutions often use a single encryption algorithm to protect display data. However, in practice, these solutions exhibit systemic flaws, such as the vulnerability of static keys to leakage, predictable initialization vectors (IVs), and weak resistance to replay attacks. For example, the long-term storage of fixed keys in general-purpose memory poses a risk of physical extraction. The lack of a dynamic update mechanism for the encryption initialization vector (IV) allows attackers to crack the encryption pattern through statistical analysis. Simple verification mechanisms are also vulnerable to man-in-the-middle attacks initiated through reverse engineering.

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

[0005] In order to solve the above technical problems, the present application is proposed. An embodiment of the present application provides an LCD security protection system based on encryption processing, which first burns the AES128 fixed key to the LCD panel 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 panel. And at the data encryption level, a paged heartbeat data structure design is used to perform data composite encryption to obtain ciphertext. Then, the ciphertext is decrypted and verified by the LCD panel and the execution action is determined. In this way, through the hardwareization of key storage, the dynamicization of initial vectors and the randomization of data structures, an LCD communication protection system with a multi-level dynamic encryption mechanism that adapts to high-security scenarios is constructed, which improves the defects of easy leakage of static keys, predictable initial vectors and weak anti-replay attack capabilities.

[0006] According to one aspect of the present application, an LCD security protection system based on encryption processing is provided, which includes: a key fixed storage module, used to burn an AES128 fixed key through an LCD panel and store it in an anti-tampering area of a security chip; an encryption initial vector acquisition module, used to obtain a dynamic encryption initial vector through a controller; a heartbeat data encryption module, used to generate heartbeat data through the controller and perform composite encryption on the heartbeat data to obtain a ciphertext; a decryption verification module, used to decrypt and verify the ciphertext through the LCD panel after receiving the ciphertext to obtain a decryption result; and an execution action module, used to determine an execution action based on the decryption result.

[0007] Compared with the prior art, the present application provides an LCD security protection system based on encryption processing. First, at the key management level, the AES128 fixed key is burned into the LCD panel and stored in the tamper-proof area of the security chip. Then, a dynamic encryption initialization vector with unpredictability and a validity period of 30 seconds is generated through handshake interaction between the controller and the LCD panel. And at the data encryption level, a paged heartbeat data structure design is used to perform data composite encryption to obtain ciphertext. Then, the ciphertext is decrypted and verified by the LCD panel and the execution action is determined. In this way, through the hardwareization of key storage, the dynamicization of initialization vectors and the randomization of data structures, an LCD communication protection system with a multi-level dynamic encryption mechanism that is adaptable to high-security scenarios is constructed, which improves the defects of easy leakage of static keys, predictable initialization vectors and weak anti-replay attack capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other purposes, features, and advantages of the present application will become more apparent through a more detailed description of the embodiments of the present application in conjunction with the accompanying drawings. The accompanying drawings are intended 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 of the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0009] Figure 1 4 is a system block diagram of an LCD security protection system based on encryption processing according to an embodiment of the present application.

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

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

[0012] Figure 44 is a block diagram of a one-time encryption subunit in an LCD security protection system based on encryption processing according to an embodiment of the present application. DETAILED DESCRIPTION

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

[0014] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0015] In addition, numerous specific details are provided in the following detailed description to better illustrate the present application. Those skilled in the art will appreciate that the present application can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present application.

[0016] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the features. Throughout the description of this application, "plurality" means two or more, unless otherwise specifically defined.

[0017] With the widespread adoption of LCD modules in financial terminals, industrial control equipment, and intelligent security systems, the security of their data transmission channels has become a critical issue. Traditional security solutions typically rely on a single encryption algorithm to protect display data. However, these solutions suffer from flaws such as the vulnerability of static keys to leakage, predictable initialization vectors, and weak resistance to replay attacks. This increases the risk of attacks through physical extraction, statistical analysis, and reverse engineering. Existing protection measures are insufficient to fully guarantee data security in scenarios involving the exchange of sensitive information.

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

[0019] This technical solution effectively addresses the key flaws of traditional LCD security solutions through a multi-layered dynamic encryption mechanism. At the key management level, a fixed AES128 key is burned into the LCD panel and stored in the tamper-proof area of the security chip. This not only blocks key extraction attacks through hardware physical protection but also mitigates the risk of long-term key leakage in general-purpose memory. To address the issue of initialization vector (IV) predictability, a dynamic encryption V(I) is generated through a handshake interaction between the controller and the LCD panel. This dynamic V(I) is unpredictable using true random number recombination technology, and a ring buffer storage mechanism with a limited validity period of 30 seconds fundamentally eliminates the possibility of replay attacks. At the data encryption level, a paged heartbeat data structure design is employed. Through differentiated fixed identification byte configuration and dual true random number injection, encrypted data packets are dynamically changing. The fixed key and dynamic V(I) are combined for encryption, maintaining the efficiency of the encryption algorithm while disrupting the statistical regularity of the encryption pattern through dynamic elements, significantly improving protection against man-in-the-middle attacks and pattern recognition cracking. The overall solution builds an LCD communication protection system that adapts to high-security scenarios through triple protection of key storage hardware, initial vector dynamicization and data structure randomization.

[0020] In the aforementioned encryption-based LCD security protection system 100, the key storage module 110 is used to burn an AES128 fixed key through the LCD panel and store it in the tamper-resistant area of the security chip. It should be understood that in traditional LCD security systems, the key storage link is often the weakest point in the entire encryption system. Because LCD modules typically use general-purpose storage media (such as Flash or EEPROM) to store encryption keys, attackers can directly extract key information through hardware attacks such as physical probing and voltage glitch injection. This is particularly true in open use scenarios such as financial terminals, where the risk of physical access to the device is significantly increased. After disassembling the device, attackers can easily obtain statically stored keys by observing the storage unit using an electron microscope or using bus sniffing tools. 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, the present application burns an AES128 fixed key through the LCD panel and stores it in the tamper-resistant area of the security chip. In other words, the tamper-resistant 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 probing, disassembly, etc. At the same time, the tamper-proof area also has the function of self-destructing or encrypting data. When abnormal physical access is detected, protective measures will be automatically taken to ensure the security of the key.

[0021] In the encryption-based LCD security protection system 100, the encryption initialization vector acquisition module 120 is configured to acquire a dynamic encryption initialization vector (DEIV) via a controller. Specifically, the DEIV acquisition module 120 is configured to: send an initial encryption handshake instruction to the LCD panel via the controller; have the LCD panel return an initialization vector (DEIV) of a predetermined number of bytes; and reassemble the DEIVs to obtain the dynamic DEIV; store the dynamic DEIV in a ring buffer via the controller. The security chip records the dynamic DEIV for a period of 30 seconds.

[0022] Specifically, the controller sends an initial encryption handshake command to the LCD panel. It should be understood that within the entire encryption-based LCD security protection system, a trusted secure channel must be established between the controller and the LCD panel. This initial encryption handshake is used to negotiate and synchronize encryption parameters (such as a dynamic encryption initialization vector) required for subsequent communication between the two parties, thereby ensuring the security of subsequent data transmission. Specifically, through this initial encryption handshake, the controller can trigger the LCD panel to generate a dynamic encryption initialization vector, avoiding the issue of predictable dynamic encryption initialization vectors and thus enhancing the security of the encryption system.

[0023] Specifically, the LCD panel returns an initialization vector of a predetermined number of bytes, and these initialization vectors are reassembled to generate the dynamic encryption initialization vector. It should be understood that in traditional security solutions, initialization vector generation often relies on unilateral logical operations in the controller. This centralized generation model has the inherent drawback of insufficient entropy. Even with the use of a random number generator, attackers can still analyze the periodicity of the random number generation algorithm or hardware noise characteristics by monitoring communication data packets over a long period of time. For example, some clock-based pseudo-random number generators have predictable statistical deviations in their output sequences within specific time windows. This hidden regularity allows attackers to establish an initialization vector prediction model using machine learning algorithms, gradually cracking the dynamic elements of the encryption system. The present application generates high-quality dynamic encryption initialization vectors by returning an initialization vector of a predetermined number of bytes through the LCD panel and reassembling these initialization vectors. It is worth noting that the present application sends a 0x05 command via the controller. Upon receiving the command, the backlight panel returns a 16-byte initialization vector (e.g., 0x0011...FF) and reassembles it into a specific byte order (big endian). In this way, refreshing the encryption vector before each heartbeat can avoid pattern recognition attacks caused by reusing the same encryption vector.

[0024] Specifically, the controller stores the dynamic encryption initialization vector in a ring buffer, and the security chip records the dynamic encryption initialization vector for a period of 30 seconds. It should be understood that the controller stores the dynamic encryption initialization vector in a ring buffer. Specifically, a ring buffer is a special data structure that features circular memory usage. During system operation, encryption operations may frequently use the dynamic encryption initialization vector. Storing it in a ring buffer eliminates the need for frequent memory allocation and release operations, improving data storage and access efficiency and reducing system overhead. The security chip records the dynamic encryption initialization vector for a period of 30 seconds to prevent security risks associated with prolonged use of the dynamic encryption initialization vector. If an initialization vector is used for an extended period, attackers may have more time and opportunities to analyze and crack it. By setting a shorter validity period, the initialization vector expires after a certain period of time, forcing the system to obtain a new dynamic encryption initialization vector, thereby increasing the randomness and security of the encryption.

[0025] Figure 2 FIG. 1 is a block diagram of a heartbeat data encryption module in an LCD security protection system based on encryption processing according to an embodiment of the present application. Figure 2As shown, in an embodiment of the present application, the heartbeat data encryption module 130 is configured to generate heartbeat data through the controller and perform compound encryption on the heartbeat data to obtain ciphertext. The heartbeat data encryption module 130 includes: a heartbeat data first page generation unit 131 for generating a first page of the heartbeat data; a heartbeat data second page generation unit 132 for generating a second page of the heartbeat data; and a ciphertext generation unit 133 for performing compound encryption on the heartbeat data based on the fixed key and the dynamic encryption initialization vector to obtain the ciphertext.

[0026] Specifically, the heartbeat data first page generation unit 131 is configured to generate the first page of heartbeat data; the heartbeat data second page generation unit 132 is configured to generate the second page of heartbeat data. More specifically, in an 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 by splitting the heartbeat data into a first page and a second page, each page contains different key information, such as a fixed identifier, a true random number, and a checksum, forming a multi-layered data structure. This design makes it difficult for an attacker 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 inclusion of the first true random number and the second true random number in the two pages, respectively, further enhances the randomness of the heartbeat data. During the encryption process, random numbers obfuscate and scramble the data, making each generated heartbeat data unique and effectively preventing replay attacks and statistical analysis attacks. It's worth noting that in one specific embodiment of this application, the heartbeat data is divided into two pages (16 + 13 bytes), each embedded with a true random number and an accumulated checksum. This dynamic paging and dual random number structure enhances replay attack resistance. The first page of heartbeat data uses a fixed string (ZXHeartBeat) combined with a true random number and checksum to ensure the legitimacy of the data source. The second page of heartbeat data uses multiple segments of true random numbers to increase entropy and enhance cracking difficulty. Specifically, the first page of heartbeat data (16 bytes) includes an 11-byte fixed identifier, a 4-byte true random number, and a 1-byte checksum. The 11-byte fixed identifier ("ZXHeartBeat") identifies the legitimate data source. The 4-byte true random number is used to prevent replay attacks. The 1-byte checksum (accumulated from the first 15 bytes) is used to quickly verify data integrity. The second page of heartbeat data (13 bytes) includes an 8-byte + 4-byte true random number and a 1-byte checksum. The 8-byte + 4-byte true random number increases randomness complexity. The 1-byte checksum (accumulated from the first 12 bytes) is used for independent verification of each page, avoiding the computational overhead of the full data.

[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 often use a single encryption algorithm to protect display data, which has systemic flaws such as easy leakage of static keys, predictable initialization vectors, and weak resistance to replay attacks. Composite encryption based on a fixed key and a dynamic encryption initialization vector can combine the advantages of both to overcome the shortcomings 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 improving the overall encryption security.

[0028] Example 1: In a specific embodiment of the present application, the ciphertext generation unit 133 is configured to perform a composite encryption of the heartbeat data using the fixed key and the dynamic encryption initialization vector using the AES128-CBC mode to obtain the ciphertext. It should be understood that AES (Advanced Encryption Standard) is a widely used symmetric encryption algorithm that is considered secure and reliable. AES128 uses a 128-bit key length. Given current computing power, the time and resources required to brute-force crack this algorithm are extremely large. However, it is effectively resistant to most known attacks and provides a solid security guarantee for heartbeat data. CBC (Cipher Block Chaining) mode is an operating mode of the AES algorithm that performs an XOR operation between the ciphertext of the previous encrypted block and the current plaintext block before encryption. This chaining feature ensures that each ciphertext block depends on all previous plaintext blocks and encryption operations. Even if the same plaintext appears in different locations, the encrypted ciphertext will be different, significantly increasing the randomness and security of the encryption and effectively resisting statistical analysis attacks. Therefore, through composite encryption in the AES128-CBC mode, the heartbeat data is converted into ciphertext. During data transmission and storage, even if the data is intercepted, an attacker without the correct fixed key and dynamic encryption initialization vector (DEV) cannot decrypt the original heartbeat data, thus ensuring that the sensitive information contained in the heartbeat data is not leaked. Thus, even if the ciphertext obtained through composite encryption is intercepted during transmission and storage, an attacker without the correct fixed key and dynamic encryption initialization vector (DEV) 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 one embodiment of the present application, zero padding and cumulative sum check (calculated independently for each page) are implemented before AES128-CBC encryption, balancing data integrity and encryption efficiency to prevent tampering and transmission errors. Then, using AES128-CBC mode, the 29-byte original data is encrypted with a fixed key (e.g., "0123456789ABCDEF") and a dynamic encryption initialization vector, generating a 32-byte ciphertext (padded with zeros to a multiple of the block size). Among them, the ciphertext is sent through the 0x06 command, and the backlight panel verifies the random number and the accumulated sum after decryption, and returns a 0x86 response (success / failure). Then, the dynamic encryption initial vector is requested in real time through an independent command (0x05), and is stored separately from the fixed key to form a dynamic + static two-factor authentication system to avoid system risks caused by the leakage of a single key. It is worth mentioning that this application combines the heartbeat interval (1 minute) with the timeout black screen strategy (2 minutes) to bind the encryption communication mechanism with the device status to realize dynamic security policy execution. The timeout black screen strategy means that if there is no heartbeat within 2 minutes, the screen will be forced to go black. This combines encryption verification to achieve double protection. True random number generation uses a hardware-level random source to ensure that attackers cannot predict the random number sequence.

[0029] More specifically, in the AES128-CBC mode encryption process, each data block (here, the heartbeat data) is first XORed with the ciphertext of the previous data block before encryption. For the first data block, it is XORed with a dynamic encryption initialization vector. This design disrupts the original data pattern, increases encryption complexity, and increases the randomness of the ciphertext. This ensures that even identical data blocks produce different ciphertext outputs, effectively preventing statistical analysis attacks. The XORed data block is then fed into the AES algorithm for encryption, using a fixed key. This entire process is repeated for each page of the heartbeat data until all pages are converted to ciphertext. The resulting ciphertext not only contains all the information in the original heartbeat data, but also, thanks to the combination of the fixed key and the dynamic encryption initialization vector, significantly enhances data confidentiality and security, ensuring that even if the data is intercepted during transmission, unauthorized third parties cannot decipher the original content. This composite encryption method leverages the powerful encryption capabilities of the AES algorithm and the chained encryption properties of CBC mode to create an efficient and secure data encryption solution.

[0030] Example 2: It's understandable that traditional encryption mechanisms still have architectural flaws when it comes to addressing advanced persistent threats. While existing encryption schemes generally employ a dynamic encryption initialization vector (IV) combined with a fixed key, their linear encryption process suffers from insufficient coupling between key elements. By separating the boundaries of the key and the VIV, attackers can implement a dual attack of key cracking and VIV prediction in stages. For example, in a system using the standard AES-CBC mode, the fixed key and dynamic VIV are linked only through a simple XOR operation. This shallow coupling allows attackers to obtain the key through a side-channel attack and then directly exploit the known VIV generation patterns to forge legitimate data packets, rendering encryption protection ineffective. More seriously, traditional encryption processes lack deep structured processing of keys and data, limiting the interaction between encryption elements to simple algorithmic overlays. When attackers analyze massive amounts of ciphertext using machine learning, they can gradually establish a correlation model between key characteristics and VIV evolution patterns, and then derive the core parameters of the encryption system through differential analysis. This systemic vulnerability is particularly fatal in a man-in-the-middle attack scenario. Attackers only need to crack a single encryption element to carry out a chain attack, which seriously dilutes the security gains of the multi-layer encryption mechanism.

[0031] Figure 3 FIG. 1 is a block diagram of a ciphertext generation unit in an LCD security protection system based on encryption processing according to an embodiment of the present application. Figure 3As shown, in an embodiment of the present application, the ciphertext generation unit 133 includes: a fixed key structured mapping subunit 1331, 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 1332, which is used to perform structured mapping encoding on the heartbeat data to obtain a heartbeat data structured mapping encoding vector; a one-time encryption subunit 1333, which is used to perform a one-time encryption based on a sparse constraint 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 one-time ciphertext; and a secondary encryption subunit 1334, which is used to perform a secondary encryption based on a sparse constraint on the dynamic encryption initial vector and the one-time ciphertext to obtain a secondary encryption interaction encoding vector as the ciphertext.

[0032] Based on this, when using AES128-CBC mode to compositely encrypt the heartbeat data with the fixed key and the dynamic encryption initialization vector to obtain the ciphertext, the technical concept of this application is to reconstruct the interactive logic of encryption elements through structured mapping coding and dual encryption architecture. During the encryption process, a nonlinear feature transformation is first performed on the fixed key to map it into a high-dimensional structured encoding vector. At the same time, the heartbeat data is converted into a multidimensional feature space representation using heterogeneous encoding rules. In the first encryption phase, the fixed key encoding vector and the data encoding vector are cross-fused in an implicit sparse constrained space to form an intermediate ciphertext with statistical analysis resistance. In the second encryption phase, a time-sensitive encoding vector of the dynamic encryption initialization vector is introduced. Dynamic perturbation encryption is performed on the intermediate ciphertext through spatial dimension reorganization, ultimately generating a composite ciphertext with dual temporal and spatial dynamic characteristics. This scheme effectively blocks the separability of the key and the encryption initialization vector, preventing attackers from launching effective attacks by cracking either element in isolation. At the same time, the irreversible nature of structured coding destroys the correlation of the training data of the machine learning model, significantly improving the defense capabilities against side-channel attacks and differential analysis.

[0033] Specifically, the fixed key structured mapping subunit 1331 is configured to perform structured mapping encoding on the fixed key to obtain a fixed key structured mapping encoding vector. Specifically, the fixed key structured mapping subunit 1331 is configured 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 the linear usage pattern of the fixed key presents a critical security vulnerability. Because the key directly participates in the encryption operation without undergoing morphological transformation, an attacker can obtain a key fragment through a side-channel attack and then reverse-derive the complete key based on the algorithm logic. Therefore, in order to transform and hide the original characteristics of the fixed key, disrupt its original structure and characteristics, and make it difficult for an attacker to analyze the characteristics and patterns of the key 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 integrated with other encryption elements in the subsequent encryption process to form a more complex encryption logic. This greatly increases the difficulty for attackers to crack the encryption system. Even if the attacker obtains part of the encrypted 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, the fixed key is subjected to structured mapping encoding based on a fully connected layer to obtain the fixed key structured mapping encoding vector. Specifically, in the structured encoding stage, the fixed key is input into a feature space transformation engine constructed by a multi-level fully connected network. The original key bit sequence is mapped to a high-dimensional continuous space through the alternating action of the linear combination of the weight matrix and the nonlinear activation function. In this process, each key bit establishes a weighted connection with all neurons in the fully connected layer. Through the nonlinear 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 encoding vector. The heartbeat data structured mapping subunit 1332 is configured to perform the fully connected layer-based structured mapping encoding on the heartbeat data to obtain the heartbeat data structured mapping encoding vector. It should be understood that, given that the heartbeat data contains a fixed-format identification field and a periodically updated checksum, its plaintext structure may retain specific statistical characteristics after encryption. For example, in a standard encryption process, the recurrence of fixed identification bits creates a regular distribution of ciphertext blocks. This structural remnant allows attackers to locate key data segments through ciphertext cluster analysis, thereby conducting selective tampering or replay attacks. Based on this, in the technical solution of the present application, the heartbeat data is structured mapped to reconstruct the data's existing form, thereby obtaining a heartbeat data structured mapping encoding vector. In particular, in a specific example of the present application, the heartbeat data is structured mapped to obtain the heartbeat data structured mapping encoding vector. Specifically, during the preprocessing phase, heartbeat data is fed into an encoding engine comprised of a multi-layer, fully connected network. This engine maps the raw byte sequence into an implicit high-dimensional feature space through a linear combination of weight matrices and a nonlinear transformation of the activation function (such as Sigmoid or Tanh). 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. True random numbers then interact nonlinearly with the network weights, generating a distribution with chaotic characteristics. This encoding process not only changes the physical storage form of the data but also mathematically reconstructs the association rules between data elements, resulting in completely heterogeneous feature space distributions for the same plaintext data in different encryption sessions.

[0035] Figure 4 FIG. 1 is a block diagram of a one-time encryption subunit in an LCD security protection system based on encryption processing according to an embodiment of the present application. Figure 4As shown, in an embodiment of the present application, the one-time encryption subunit 1333 is used to perform a one-time encryption based on a sparse constraint on the heartbeat data structured mapping code vector based on the fixed key structured mapping code vector to obtain a fixed key-heartbeat data interaction code vector as the one-time ciphertext. Among them, the one-time encryption subunit 1333 includes: a one-dimensional convolution feature phase space reconstruction secondary subunit 1333-1, which is used to perform one-dimensional convolution feature phase space reconstruction on the fixed key structured mapping code vector and the heartbeat data structured mapping code vector to obtain a set of fixed key local structured mapping code vectors and a set of heartbeat data local structured mapping code vectors; a fixed key-heartbeat data implicit interaction association secondary subunit 1333-2, which is used to calculate the implicit interaction association matrix between each group of corresponding fixed key local structured mapping code vectors and heartbeat data local structured mapping code vectors in the set of fixed key local structured mapping code vectors and the set of heartbeat data local structured mapping code vectors to obtain a set of fixed key-heartbeat data implicit interaction association matrices; a spatial sparse constraint weighted aggregation secondary subunit 1333-3, which is used to perform spatial sparse constraint factor weighted aggregation processing on the set of fixed key-heartbeat data implicit interaction association matrices to obtain the fixed key-heartbeat data interaction code vector. It should be understood that the interaction mode between the key and the data has a fatal linear coupling defect. 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 of 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, the data encryption path can be deduced through reverse engineering, and then a legitimate data packet can be forged. This linear interaction mode is particularly vulnerable to machine learning analysis. By training a deep neural network, the attacker can establish an association model between the key characteristics and the ciphertext form, and ultimately achieve reverse deduction of the encryption logic. Therefore, the present application performs a sparse constraint-based one-time encryption on the heartbeat data structured mapping code vector based on the fixed key structured mapping code vector to obtain a fixed key-heartbeat data interaction code vector as the one-time ciphertext. In other words, the fixed key-heartbeat data interactive encoding vector obtained through a one-time encryption serves as the one-time ciphertext. This incorporates the characteristics of both the fixed key and the heartbeat data, and undergoes complex interactive processing. This makes it nearly impossible for an attacker to recover the original fixed key and heartbeat data from the one-time ciphertext without the correct decryption method and key, greatly improving 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 code vector and the heartbeat data structured mapping code vector to obtain a set of fixed key local structured mapping code vectors and a set of heartbeat data local structured mapping code vectors, which are expressed as a one-dimensional convolutional feature phase space reconstruction formula: ;in, is the fixed key structured mapping encoding vector, is the heartbeat data structured mapping encoding vector, To reconstruct the one-dimensional convolution feature phase space, and are the first, second, and third in the set of fixed key local structured mapping encoding vectors. and A fixed-key locally structured mapping encoding vector, is a set of fixed-key locally structured mapping encoding vectors, and are the first, second, and third vectors in the set of local structured mapping encoding vectors of heartbeat data. and Heartbeat data local structured mapping encoding vector, is a set of local structured mapping encoding vectors of heartbeat data, and and The lengths are the same. It's understandable that traditional encryption schemes often have potential security flaws when processing the feature interactions between fixed keys and heartbeat data due to ignoring local dependencies within the vectors. As static, high-dimensional feature representations, the global feature distributions of the fixed-key structured mapping code vector and the heartbeat data structured mapping code vector make it difficult to directly reveal implicit local structural correlations. Based on the phase space reconstruction principle of dynamical systems theory, a delayed embedding mechanism simulating dynamic trajectories is required to map the static feature vectors into an abstract feature space with potential spatiotemporal correlations. One-dimensional convolution, through local perception and nonlinear transformation in the form of a sliding window, effectively explores the hidden dimensional correlations and patterns within the feature vectors, thereby addressing the limitations of traditional methods, such as the single feature interaction pattern and insufficient resistance to reverse engineering. Through one-dimensional convolutional feature phase space reconstruction, the high-dimensional global feature vectors of the fixed-key and heartbeat data features can be decomposed into a set of multiple sets of local structured mapping code vectors: a set of fixed-key local structured mapping code vectors and a set of heartbeat data local structured mapping code vectors. By introducing a convolution kernel weight learning mechanism and nonlinear mapping of the activation function, the original feature space is upgraded to a more expressive implicit space. Each convolution kernel acts as a pattern-specific feature detector, capturing local structural information within the vector from different perspectives, generating a set of local feature representations with multimodal properties. This process not only enhances the ability to model local dependencies within features but also builds feature redundancy through distributed representation, forming a robust feature system that is resistant to noise interference and local tampering, providing a nonlinearly separable input foundation for subsequent encrypted interactions. In this way, the global feature vectors of the fixed key features and heartbeat data features are reconstructed into a feature set containing multi-scale local structural information: a set of fixed key local structured mapping encoding vectors and a set of heartbeat data local structured mapping encoding vectors. Each local structured mapping encoding feature corresponds to an abstract pattern feature perceived by a specific convolution kernel, breaking the linear separability of the original features through nonlinear transformation. The multi-perspective representation set generated by multiple sets of convolution kernels operating in parallel forms a distributed encoding system that covers interaction patterns of features at different granularities. The feature redundancy mechanism effectively improves the model's tolerance to noisy data and partial feature tampering, while the explicit modeling of local structure strengthens the nonlinear coupling between encryption elements. This reconstruction process makes it difficult for attackers to restore the original feature distribution 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 association secondary subunit 1333-2 is used to calculate the implicit interaction association matrix between each corresponding fixed key local structured mapping code vector and heartbeat data local structured mapping code vector in the set of the fixed key local structured mapping code vector and the set of the heartbeat data local structured mapping code vector to obtain a set of fixed key-heartbeat data implicit interaction association matrices, which is expressed as a fixed key-heartbeat data implicit interaction association formula: ;in, is the transpose operation, and They are and The corresponding weight matrix, is matrix multiplication, yes and The length of the vector after multiplication, yes and The fixed key-heartbeat data implicit interaction association matrix between them. It should be understood that although the set of fixed key local structured mapping encoding vectors and the set of heartbeat data local structured mapping encoding vectors contain multi-perspective local features, the potential correlation between their dimensions is still implicit in the linear or shallow nonlinear space. In order to break through the limitations of the predefined interaction space, it is necessary to construct a dynamic implicit query space in a data-driven manner to map the interaction relationship between feature pairs to a high-dimensional implicit association domain. By introducing an implicit query mechanism based on model parameter encoding, the deep nonlinear 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 the traditional method of single feature interaction mode, poor interpretability and weak anti-reverse engineering ability. Specifically, by projecting each set of feature pairs to the implicit association domain, the linear combination and nonlinear transformation of the weight matrix are used to generate a set of fixed key-heartbeat data implicit interaction association matrices that characterize the multidimensional interaction strength between the two. Each fixed key-heartbeat data implicit interaction correlation matrix, as a mathematical abstraction of cross-modal feature associations, not only quantifies the coupling strength between local feature dimensions but also reconstructs the mathematical expression of the interaction logic through the distributed encoding mechanism of the implicit space. This process overcomes the expressive limitations of explicit interaction functions, establishing an association bridge between feature pairs that is resistant to reverse analysis, providing an intermediate representation that is both inseparable and nonlinearly separable for the subsequent deep integration of encryption elements. Here, each fixed key-heartbeat data implicit interaction correlation matrix uses a nonlinear mapping in the implicit query space to upgrade the linear correlation between the original feature pairs to a high-dimensional abstract association domain, forming interaction features that are resistant to pattern recognition attacks. The dynamic generation mechanism of the implicit space prevents attackers from reverse-engineering the interaction logic through fixed algorithms, while the multi-dimensional association characteristics of the elements within the matrix effectively mask the action paths of a single feature dimension. As an intermediate carrier for deep coupling of encryption elements, this set not only retains the fine-grained interactive information of local features, but also destroys the separability of keys and data in traditional encryption processes through implicit encoding, significantly enhancing the encryption system's ability to resist side-channel attacks and differential analysis, and laying the core data foundation for building a multi-layer dynamic encryption mechanism.

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

[0039] Specifically, a differential manifold structured optimization is performed on each fixed key-heartbeat data implicit interaction association matrix in the set of fixed key-heartbeat data implicit interaction association matrices to obtain a set of optimized fixed key-heartbeat data implicit interaction association matrices, which is expressed as follows using a differential manifold structured optimization formula: ;in, yes The eigenvalues, yes The eigenvalues, The natural constant The exponential function value with base , yes and Fixed key between - heartbeat data implicit interaction associated with relative phase, is each eigenvalue in the fixed key-heartbeat data implicit interaction phase covariance matrix, yes and The fixed key between the heartbeat data implicitly interacts with the phase covariant matrix, yes The inverse matrix of yes The optimized fixed key-heartbeat data implicit interaction matrix. It should be understood that although the set of fixed key-heartbeat data implicit interaction matrices contains multi-dimensional interaction relationships, its original nonlinear correlation pattern is non-integrable and local coordinate dependent at the global geometric level, resulting in dynamic instability in the encryption element coupling mechanism. In order to eliminate the local topological distortion effect in the nonlinear manifold space, it is necessary to establish an affine connection framework through differential geometry theory to map the fixed key-heartbeat data implicit interaction matrix to a canonical space with a flat connection structure, so as to solve the core defects of the traditional method of uncontrollable feature interaction paths and weakened anti-reverse analysis capabilities due to differences in manifold curvature. Through the differential manifold structured optimization technology, the geometric topological characteristics of the fixed key-heartbeat data implicit interaction matrix can be reconstructed to achieve the standardized expression of the feature interaction dynamics model in the connection flat space. Specifically, based on the fixed key-heartbeat data implicit interaction phase covariant matrix The affine transformation mechanism is used to map the feature pairs after phase space reconstruction to the fixed key local structured encoding vector and heartbeat data local structured mapping encoding vector The local nonlinear correlation pattern is converted into a globally integrable differential manifold structure, eliminating the covariant differential distortion caused by coordinate transformation. By constructing a fixed key-heartbeat data implicit interactive correlation phase covariant matrix and its inverse matrix The interaction optimization system, while maintaining the invariance of the characteristic interaction morphism transmission, strips away redundant high-order nonlinear interactions, establishing a manifold dynamics mapping model with minimal computational complexity, ensuring that the encryption element interaction logic satisfies Lie group symmetry constraints and 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 differential manifold representation system with a flat connection structure. The introduction of the phase covariant matrix enables the characteristic interaction path to maintain covariant differential invariance in local affine coordinates, eliminating the interference of nonlinear manifold curvature on the encryption element coupling mechanism. The optimized set of fixed key-heartbeat data implicit interaction correlation matrices is mapped into a normalized connection space, compressing the original high-dimensional nonlinear interaction pattern into a low-dimensional, resolvable geometric topological structure, significantly reducing the computational redundancy of the characteristic interaction modeling.

[0040] Specifically, the square of the Frobenius norm of each optimized fixed key-heartbeat data implicit interaction association matrix in the set of optimized fixed key-heartbeat data implicit interaction association matrices is calculated to obtain a set of fixed key-heartbeat data implicit interaction space constraint factors, which is expressed as a fixed key-heartbeat data implicit interaction space constraint factor calculation formula: ;in, To calculate the square of the matrix Frobenius norm, yes 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 squared norm value directly represents the order of magnitude and distribution density of significant interaction elements in the matrix, providing a mathematical benchmark for objectively quantifying the strength of sparsity. This process eliminates the interference of matrix dimension and local noise through standardized measurement methods, 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, the set of fixed key-heartbeat data implicit interaction space constraint factors is normalized based on the softmax function to obtain a set of fixed key-heartbeat data implicit interaction space sparse constraint factors, which is expressed as the fixed key-heartbeat data normalization processing formula: ;in, yes function, yes The corresponding fixed key-heartbeat data implicit interaction space sparse constraint factors. It should be understood that although the set of fixed key-heartbeat data implicit interaction space constraint factors quantifies the sparsity of the optimized association matrix through norm calculation, the distribution range of their absolute values is inconsistent. Directly using them for aggregation can easily lead to the problem of high-sparse matrices being weakened by low weights or low-sparse noise being mistakenly enhanced. In order to establish a unified probabilistic weight distribution standard and strengthen the guiding role of the sparsity prior assumption on the interaction logic of encrypted elements, it is necessary to map the constraint factor set to a normalized probability space through the softmax function to address the defect of the static weight distribution mechanism in traditional methods that cannot dynamically adapt to the importance of feature interaction patterns. By converting 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 distribution mechanism based on sparsity strength can be constructed. Specifically, through the exponential transformation and normalization 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. This allows the high-sparsity optimized fixed key-heartbeat data implicit interaction correlation matrix to dominate the aggregation process, while the contribution 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 distribution through probability space mapping, while enforcing the constraint that the sum of weights must be 1. This ensures that the fusion process of encrypted element interaction information not only focuses on key feature correlation patterns but also conforms to mathematical norms, providing a dynamic weight benchmark that is noise-resistant and interpretable for subsequent weighted aggregation. The probabilistic nature of the normalized weights enhances the model's interpretability of feature interaction patterns, and visualization of the distribution of the sparse constraint factors in the fixed key-heartbeat data implicit interaction space clearly reveals the core correlation dimensions between encrypted elements.

[0042] Specifically, based on the set of fixed key-heartbeat data implicit interaction spatial sparse constraint factors, the set of optimized fixed key-heartbeat data implicit interaction association matrices is weightedly aggregated to obtain the fixed key-heartbeat data interaction encoding vector, which is expressed as a fixed key-heartbeat data weighted aggregation formula: ;in, is the fixed key-heartbeat data interaction encoding matrix, It's reshaping. is the fixed key-heartbeat data interaction encoding vector. It should be understood that while optimizing the set of fixed key-heartbeat data implicit interaction correlation matrices improves the characterization quality of local interaction patterns through manifold optimization and sparsity constraints, its heterogeneous distribution characteristics make it difficult to effectively distinguish high-value encryption elements from inefficient noise signals through direct arithmetic averaging or simple splicing. To overcome 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 strength of the matrix as a quantification standard for information value, to address the core issues of weakened encryption element interaction logic and insufficient anti-attack capabilities caused by fixed weight distribution. Through sparsity-driven adaptive weighted aggregation technology, it is possible to achieve information value screening and deep fusion of the set of optimized fixed key-heartbeat data implicit interaction correlation matrices. Specifically, based on the dynamic weighting of a set of sparsity-constrained factors in the fixed-key-heartbeat data implicit interaction space, the sparsity strength of each optimized fixed-key-heartbeat data implicit interaction matrix is mapped to its contribution weight in the aggregation process, allowing the core encryption element interaction patterns represented by high-sparsity matrices to dominate the generation of the final feature encoding vector. This process, leveraging the positive correlation between weight and sparsity, constructs a hierarchical fusion mechanism for encryption element interaction information, suppressing the interference of inefficient or redundant interaction noise on the encryption logic and ensuring that the aggregation results are precisely focused on key feature interaction paths that are resistant to reverse analysis. This provides a high-purity and robust interaction encoding foundation for building a multi-level dynamic encryption system. In this way, the sparsity-constrained dynamic weighting mechanism undermines the separability of traditional encryption elements, significantly improving the encryption system's defenses against side-channel attacks and differential analysis, while also providing a mathematically consistent feature interaction map for interpretability verification of encryption logic. This step does not simply average or concatenate multiple optimized fixed key-heartbeat data implicit interaction association matrices, but performs weighted fusion based on the fixed key-heartbeat data implicit interaction space sparse constraint factor. This weighted fusion is dynamically adaptive, and the weight size depends entirely on the fixed key-heartbeat data implicit interaction space sparse constraint factor of each optimized fixed key-heartbeat data implicit interaction association matrix.

[0043] Specifically, the secondary encryption subunit 1334 is configured to perform sparsity-constrained secondary encryption on the dynamic encryption initialization vector and the primary ciphertext to obtain a secondary encrypted interaction code vector as the ciphertext. It should be understood that, given that the interaction between the dynamic encryption initialization vector and the intermediate ciphertext often utilizes linear superposition, this shallow correlation allows attackers to gradually decipher the encryption elements through separation and parsing techniques. Even if the primary encryption process possesses high security, if the secondary encryption stage still utilizes simple computational schemes (such as XOR or linear transformation), attackers can still establish a prediction model by intercepting the correlation between the dynamic encryption initialization vector and the secondary ciphertext. For example, in a standard multi-layer encryption system, if the secondary encryption key and the dynamic encryption initialization vector have a fixed algorithmic correlation, attackers can decipher the dynamic encryption initialization vector generation pattern and reverse engineer the encryption logic, rendering the multi-layer protection mechanism ineffective. This systemic flaw stems from the lack of nonlinear coupling and dynamic correlation blocking mechanisms between encryption elements. Therefore, the present application performs sparsity-constrained secondary encryption on the dynamic encryption initialization vector and the primary ciphertext to obtain a secondary encrypted interaction code vector as the ciphertext. In this way, the secondary encrypted interactive encoding vector (i.e., ciphertext) obtained through secondary encryption combines the characteristics of the primary ciphertext and the dynamic encryption initialization vector, and undergoes complex feature interaction processing. This makes it nearly impossible for an attacker to recover the original heartbeat data and fixed key from the ciphertext without the correct dynamic encryption initialization vector and the corresponding decryption algorithm, greatly improving encryption security and protecting the confidentiality of sensitive information in the system. In particular, the dynamic nature of the dynamic encryption initialization vector ensures that the initialization vector used for each encryption is different. Even if an attacker intercepts the ciphertext and attempts a replay attack, the replayed ciphertext cannot pass decryption verification because the dynamic encryption initialization vector used by the receiver has been updated. This effectively prevents replay attacks and ensures the authenticity and validity of data transmission.

[0044] In the encryption-based LCD security protection system 100 described above, the decryption verification module 140 is configured to, upon receiving the ciphertext, perform decryption verification on the ciphertext through the LCD panel to obtain a decryption result. It should be understood that during data transmission, ciphertext may be intercepted, tampered with, or forged by an attacker. By performing decryption verification on the ciphertext, the LCD panel can determine whether the received ciphertext is encrypted from the original data sent by the legitimate sender, thereby ensuring the data's authenticity. Only verified authentic data can be correctly processed and used by the system, avoiding system failures or security incidents caused by the use of false data. One of the main purposes of decryption verification is to recover the original heartbeat data from the ciphertext. This decryption verification step effectively identifies and protects against various security threats, such as data tampering, forgery, and replay attacks. By rigorously verifying the ciphertext, the system can promptly detect abnormal data and take appropriate measures to prevent security vulnerabilities from being exploited, thereby enhancing the overall security of the system. Specifically, the LCD panel uses AES128-CBC mode for decryption. This mode requires that each ciphertext block be XORed with the output of the previous ciphertext block before decryption. For the first data block, this is directly XORed with the dynamic encryption initialization vector. This process effectively reverses the transformations performed during the encryption phase, allowing accurate recovery of the original information even if the same plaintext data produces 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 cumulative checksums, to ensure that the data has not been tampered with. The checksum calculation covers various components of the heartbeat data, such as fixed identifiers and true random numbers, thereby ensuring the integrity of the decrypted data. Once all data blocks have been successfully decrypted and verified, the LCD panel can restore the original heartbeat data from the ciphertext and confirm its legitimacy and accuracy.

[0045] In the encryption-based LCD security protection system 100, the action execution module 150 is configured to determine an action based on the decryption result. It should be understood that in the encryption-based LCD security protection system, after decrypting and verifying the ciphertext, the decryption result reflects whether the received data is authentic, complete, and legal. Determining the action based on the decryption result allows the system to respond promptly to various situations and ensure secure and stable operation. For example, if the decryption result indicates that the data has been tampered with, the system can take appropriate measures to prevent malicious attacks and safeguard 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 an alarm, adjust the camera angle, or update access rights to the access control system. On the other hand, if the decryption result reveals data anomalies, such as signs of tampering or failure to pass checksum verification, the system will implement a series of defensive measures to prevent potential security threats. These measures may include, but are not limited to, immediately terminating the current session, logging the error for subsequent analysis, sending a warning notification to the administrator, and automatically entering safe mode to restrict unauthorized access. For devices designed with a timeout black screen policy, the system may also force the screen to shut down if the number of decryption failures exceeds a preset threshold, providing an additional safeguard against sensitive information leakage. Determining actions based on decryption results not only ensures normal system operation but also effectively defends against various attack attempts, maintaining overall system security and reliability. By accurately evaluating decryption results and responding promptly, this mechanism provides a solid security foundation for critical applications involving LCD display modules.

[0046] In summary, the LCD security protection system 100 based on encryption processing according to the embodiment of the present application is explained. At the key management level, the AES128 fixed key is burned into the LCD panel and stored in the tamper-proof area of the security chip. Then, a dynamic encryption initialization vector with unpredictability and a validity period of 30 seconds is generated through handshake interaction between the controller and the LCD panel. At the data encryption level, a paged heartbeat data structure design is used to perform data composite encryption to obtain ciphertext. Then, the ciphertext is decrypted and verified by the LCD panel and the execution action is determined. In this way, through the hardwareization of key storage, the dynamicization of initialization vectors, and the randomization of data structures, an LCD communication protection system with a multi-level dynamic encryption mechanism that is adaptable to high-security scenarios is constructed, which improves the defects of static keys that are easy to leak, initialization vectors that are predictable, and weak resistance to replay attacks.

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

[0048] Alternatively, in another example, the encryption-based LCD security protection system 100 and the terminal device may also be separate devices, and the encryption-based LCD security protection system 100 may be connected to the terminal device via a wired and / or wireless network and transmit interactive information in accordance with an agreed data format.

Claims

1. An LCD security protection system based on encryption processing, characterized in that: include: A key fixed storage module is used to burn the AES128 fixed key through the LCD panel and store it in the tamper-proof area of the security chip; An encryption initial vector acquisition module is used to obtain a dynamic encryption initial vector through a controller; a heartbeat data encryption module is used to generate heartbeat data through the controller and perform compound encryption on the heartbeat data to obtain ciphertext; a decryption verification module, configured to, after receiving the ciphertext, perform decryption verification on the ciphertext through the LCD panel to obtain a decryption result; An execution action module, configured to determine an execution action based on the decryption result; The heartbeat data encryption module includes: a heartbeat data first page generation unit for generating the first page of the heartbeat data; a heartbeat data second page generation unit for generating the second page of the heartbeat data; and a ciphertext generation unit for performing composite encryption on the heartbeat data based on the fixed key and the dynamic encryption initialization vector to obtain the ciphertext. Among them, 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 one-time encryption subunit, which is used to perform a sparse constraint-based one-time encryption 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 a one-time ciphertext; and a secondary encryption subunit, which is used to perform a sparse constraint-based secondary encryption on the dynamic encryption initial vector and the one-time ciphertext to obtain a secondary encryption interaction encoding vector as the ciphertext.

2. The LCD security protection system based on encryption processing according to claim 1, characterized in that: The encryption initialization vector acquisition module is configured to: send an initial encryption handshake instruction to the LCD panel via the controller; return an initialization vector of a predetermined number of bytes via the LCD panel, and reassemble the initialization vector of the predetermined number of bytes to obtain the dynamic encryption initialization vector; store the dynamic encryption initialization vector in a ring buffer via the controller, with the security chip recording the dynamic encryption initialization vector for a validity period of 30 seconds.

3. The LCD security protection system based on encryption processing according to claim 2, 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.

4. The LCD security protection system based on encryption processing according to claim 3, characterized in that: The ciphertext generation unit is configured to: use the AES128-CBC mode to perform composite encryption on the heartbeat data with the fixed key and the dynamic encryption initialization vector to obtain the ciphertext.

5. The LCD security protection system based on encryption processing according to claim 4, characterized in that: The fixed key structured mapping subunit is configured to perform structured mapping encoding based on a fully connected layer on the fixed key to obtain the fixed key structured mapping encoding vector.

6. The LCD security protection system based on encryption processing according to claim 5, characterized in that: The heartbeat data structured mapping subunit is configured to perform the fully connected layer-based structured mapping encoding on the heartbeat data to obtain the heartbeat data structured mapping encoding vector.

7. The LCD security protection system based on encryption processing according to claim 6, characterized in that: The one-time encryption subunit includes: a one-dimensional convolutional feature phase space reconstruction secondary subunit, which is used to perform one-dimensional convolutional feature phase space reconstruction on the fixed key structured mapping code vector and the heartbeat data structured mapping code vector to obtain a set of fixed key local structured mapping code vectors and a set of heartbeat data local structured mapping code vectors; a fixed key-heartbeat data implicit interaction association secondary subunit, which is used to calculate the implicit interaction association matrix between each corresponding set of fixed key local structured mapping code vectors and heartbeat data local structured mapping code vectors in the set of fixed key local structured mapping code vectors and the set of heartbeat data local structured mapping code vectors to obtain a set of fixed key-heartbeat data implicit interaction association matrices; a spatial sparse constraint weighted aggregation secondary subunit, which is used to perform spatial sparse constraint factor weighted aggregation processing on the set of fixed key-heartbeat data implicit interaction association matrices to obtain the fixed key-heartbeat data interaction code vector.

8. The LCD security protection system based on encryption processing according to claim 7, characterized in that: The spatial sparse constraint weighted aggregation secondary subunit is used to: perform differential manifold structured optimization on each fixed key-heartbeat data implicit interaction association matrix in the set of fixed key-heartbeat data implicit interaction association matrices to obtain a set of optimized fixed key-heartbeat data implicit interaction association matrices; Calculating the square of the Frobenius norm of each optimized fixed key-heartbeat data implicit interaction association matrix in the set of optimized fixed key-heartbeat data implicit interaction association matrices to obtain a set of fixed key-heartbeat data implicit interaction space constraint factors; Performing a normalization process based on a 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 spatial sparse constraint factors, weighted aggregation is performed on the set of optimized fixed key-heartbeat data implicit interaction association matrices to obtain the fixed key-heartbeat data interaction encoding vector.

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