Wireless mouse data secure transmission method based on Polar code and chaotic encryption

Abstract

The invention relates to a wireless mouse data secure transmission method based on Polar codes and chaotic encryption. The wireless mouse data secure transmission method comprises the following steps: iteratively generating a dynamic key sequence through a Logistic mapping chaotic system; according to the mouse original data blocking result and the dynamic key sequence, determining a preprocessed data block; dynamically generating a channel polarization matrix according to the chaotic sequence value; according to the channel capacity characteristics and the data priority index of the channel polarization matrix, calculating the distribution priority of each bit position through a balance factor; carrying out Polar coding according to the preprocessed data block, the channel polarization matrix and the distribution priority, and carrying out superposition chaotic phase modulation to generate an encrypted signal; and performing phase demodulation on the received encrypted signal according to the synchronous chaos sequence, and recovering original data by using the reconstruction polarization matrix through a list decoding algorithm to obtain a reconstructed data block. According to the invention, the data transmission safety and reliability of the wireless mouse can be improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular to a wireless mouse data security transmission method based on Polar codes and chaotic encryption, an electronic device, and a non-transient computer-readable storage medium. Background Art

[0002] Currently, wireless mice commonly use 2.4GHz wireless communication or Bluetooth technology to interact with computers. Data is sampled and processed on the mouse side before being sent to the receiver via a wireless module, completing the transmission of commands such as cursor movement and button clicks. To achieve basic data encryption and anti-interference capabilities, some products use simple symmetric encryption algorithms (such as AES-128) or CRC checksums to ensure data integrity and confidentiality.

[0003] However, traditional encryption algorithms have high computational overhead for resource-constrained embedded devices, making it difficult to achieve high-strength, low-latency data encryption in low-power, compact wireless mice. Furthermore, current anti-interference mechanisms primarily rely on physical layer techniques, failing to enhance data robustness at the coding layer. These mechanisms are susceptible to multipath interference, channel noise, and intentional jamming, leading to increased bit error rates or connection loss. Summary of the Invention

[0004] In response to the technical problems existing in the prior art, the present invention provides a wireless mouse data security transmission method based on Polar code and chaotic encryption, an electronic device and a non-transient computer-readable storage medium, which can improve the security of wireless mouse data transmission.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] The present invention provides a wireless mouse data security transmission method based on Polar code and chaotic encryption, comprising:

[0007] According to the preset bifurcation parameters, initial values and time decay coefficients, a dynamic key sequence is generated through the iterative Logistic mapping chaotic system.

[0008] Determine a pre-processed data block according to the mouse original data block result and the dynamic key sequence;

[0009] Dynamically generate channel polarization matrix according to chaotic sequence values;

[0010] Calculating the allocation priority of each bit position using a balancing factor according to the channel capacity characteristics and data priority index of the channel polarization matrix;

[0011] Performing polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal;

[0012] The received encrypted signal is phase-demodulated according to the synchronized chaotic sequence, and the original data is restored by using a list decoding algorithm using a reconstructed polarization matrix to obtain a reconstructed data block.

[0013] Optionally, the iterative generation of a dynamic key sequence through a Logistic mapping chaotic system according to a preset bifurcation parameter, initial value, and time decay coefficient includes:

[0014] Get the current state value representing the state of the chaotic system at each iteration;

[0015] Constructing a Logistic chaos term according to the bifurcation parameter and the current state value;

[0016] Construct an exponential decay modulation term based on the time decay coefficient and the system time variable;

[0017] The dynamic key sequence is iteratively generated according to the Logistic chaos term and the exponential decay modulation term.

[0018] Optionally, the dynamic key sequence is expressed as:

[0019] x(n+1)=μ·x(n)·(1―x(n))·exp(―αt)

[0020] Where x(n+1) is the dynamic key sequence, x(n) is the current state value, μ is the bifurcation parameter, α is the time decay coefficient, and t is the system time variable.

[0021] Optional, including:

[0022] Map the original data block according to the mapping coefficient matrix to construct the original data linear mapping item;

[0023] Constructing the chaotic disturbance weighted term according to the chaotic weight factor and chaotic sequence value;

[0024] The pre-processed data block is obtained according to the original data linear mapping item and the chaotic disturbance weighting item.

[0025] Optionally, the preprocessed data block is represented as:

[0026] D(i)=β·M(i)+γ·x(i)mod256

[0027] Where D(i) is the preprocessed data block, M(i) is the original data block, x(i) is the i-th chaotic sequence value, β is the mapping coefficient matrix, and γ is the chaotic weight factor.

[0028] Optionally, dynamically generating a channel polarization matrix according to the chaotic sequence value includes:

[0029] The basic polarization kernel matrix is processed based on the Kronecker product to obtain the processed recursive expansion term;

[0030] Get the rotation matrix of the chaotic sequence value of the nth iteration;

[0031] The channel polarization matrix is generated according to the recursive expansion term and the rotation matrix.

[0032] Optionally, the allocation priority of each bit position is calculated by a balance factor according to the channel capacity characteristics and data priority index of the channel polarization matrix.

[0033] Process the sub-channel capacity according to the balance factor to construct the channel capacity term;

[0034] Constructing a data importance item according to the balance factor and the data importance indicator;

[0035] The allocation priority is determined according to the channel capacity item and the data importance item.

[0036] Optionally, performing polar encoding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal includes:

[0037] Performing Polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority to construct a coding item;

[0038] Perform chaotic phase modulation on the chaotic sequence to construct encryption terms;

[0039] The encrypted signal is generated according to the encoding item and the encryption item.

[0040] Optionally, phase demodulating the received encrypted signal according to the synchronized chaotic sequence, restoring the original data by a list decoding algorithm using a reconstructed polarization matrix, and obtaining a reconstructed data block includes:

[0041] Performing exponential processing on the phase demodulation function of the chaotic sequence to obtain an exponential phase demodulation function, and processing the encrypted signal based on the exponential phase demodulation function to construct a phase demodulation term;

[0042] Processing the phase demodulation term using the reconstructed polarization matrix to construct a polarization decoding term;

[0043] The polarization decoding items are used to restore original data through a list decoding algorithm to obtain the reconstructed data block.

[0044] Optionally, the step of dynamically generating the chaotic sequence includes:

[0045] The receiving end uses the same bifurcation parameters and time decay coefficient as the sending end;

[0046] Transmitting an encrypted seed of the initial value of the chaotic system through a secure channel;

[0047] The receiving end decrypts according to the encryption seed and synchronously executes the chaotic sequence generation process with the same number of iterations.

[0048] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby realizing a wireless mouse data security transmission method based on Polar code and chaotic encryption as described above.

[0049] In addition, to achieve the above-mentioned purpose, the present invention also proposes a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by the processor, it implements the wireless mouse data security transmission method based on Polar code and chaotic encryption as described above.

[0050] In summary, this invention not only offers the advantages of high encryption strength, strong error tolerance, a compact system structure, and wide adaptability, but also integrates modern communication coding theory with chaotic dynamics theory to create an innovative wireless terminal data protection mechanism. This effectively meets the dual requirements of "high efficiency and high security" for terminals such as wireless mice, providing solid technical support for the communication security of the next generation of lightweight smart devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A flowchart of a wireless mouse data security transmission method based on Polar code and chaotic encryption provided by the present invention;

[0052] Figure 2 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0053] Figure 3 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0054] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0055] In the description of the present invention, 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. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0056] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0057] See also Figure 1 , provides a flowchart of a wireless mouse data security transmission method based on Polar code and chaotic encryption of the present invention, comprising the following steps:

[0058] Step 101: Generate a dynamic key sequence through the iterative Logistic map chaotic system according to the preset bifurcation parameter, initial value and time decay coefficient.

[0059] In some embodiments, step 101 may include:

[0060] Get the current state value representing the state of the chaotic system at each iteration;

[0061] Constructing a Logistic chaos term according to the bifurcation parameter and the current state value;

[0062] Construct an exponential decay modulation term based on the time decay coefficient and the system time variable;

[0063] The dynamic key sequence is iteratively generated according to the Logistic chaos term and the exponential decay modulation term.

[0064] Among them, the dynamic key sequence is expressed as:

[0065] x(n+1)=μ·x(n)·(1―x(n))·exp(―αt)

[0066] Where x(n+1) is the dynamic key sequence, x(n) is the current state value, μ is the bifurcation parameter, α is the time decay coefficient, and t is the system time variable.

[0067] In practice, this formula is used to generate a dynamic key sequence, a core component of the chaotic encryption mechanism in this scheme. Based on the logistic mapping model, it introduces a time-decaying modulation term, forming an extended chaotic system with enhanced nonlinearity, time correlation, and system sensitivity. Its output, x(n+1), generates a new key fragment within each iteration, serving as the basis for subsequent multi-stage processing, including data perturbation, channel perturbation, and phase modulation.

[0068] x(n) represents the state of the chaotic system at the nth iteration and is part of the key sequence, equivalent to the chaotic sequence value at the nth iteration. x(n+1) represents the next state value derived from the current state and serves as the input of the encrypted perturbation sequence. μ ranges from [3.57, 4] and controls the complexity of the system's chaotic behavior; the closer it is to 4, the stronger the chaos. α controls the system's energy decay over time and is used to prevent long-term repetitive and static attacks. t can be the system's operating step size, logic cycle, or pseudo-time for exponential modulation.

[0069] μ·x(n)·(1-x(n)) is the logistic chaos term, an expression of the classic logistic map and the mathematical foundation of chaotic sequences. Its behavior is highly sensitive to initial values (i.e., initial value sensitivity). When μ∈[3.57,4], the system enters a strongly chaotic state, and the output sequence exhibits pseudorandomness. This achieves exponential growth of the key space and unpredictable trajectory.

[0070] exp(―αt) is an exponential decay modulation term, which introduces time dependence, that is, the same initial state generates different key values at different times; it effectively prevents attackers from inferring the system through offline training or static observation; the value of α regulates the system's "memory" and can be set to gradual change, periodic reset, or adaptive update; it enhances the use of temporary keys, giving the system a "key decay" feature.

[0071] This method is sensitive to initial values. The system outputs completely different results after multiple iterations for a small deviation in the initial value. It is also unpredictable. It is impossible to predict future outputs from past outputs. This is the core security feature of chaotic systems. It has a high-complexity key space. The theoretical key space of chaotic sequences can reach 2 under 64-bit floating point representation. 64 . It has time modulation anti-replay, even if the attacker obtains the key once, he cannot reproduce the same output in the next iteration.

[0072] It can be understood that the chaotic sequence value x(n) is the "raw material" for subsequent modules such as data perturbation, channel perturbation (rotation matrix), and phase encryption. The overall security of the system benefits from its high nonlinearity, randomness, and non-reconstruction. By sharing the initialization parameters x(0), μ, and α between the sender and receiver and performing parallel iterative synchronization at both ends, the system can eliminate the need to transmit the entire key stream, only a small amount of parameter seeds, reducing communication overhead and lowering the risk of leakage.

[0073] This method has adjustable and controllable characteristics and is adaptable to different application scenarios. For example, adjusting μ can control the degree of chaos in the system; adjusting α can control the timeliness of the key; changing the initial value x(0) can achieve a one-time key (OTP) or periodic key refresh; therefore, this scheme has good flexibility and scalability.

[0074] Due to the addition of time variables, the same state outputs different keys at different times; after the exponential modulation and nonlinear chaotic terms are superimposed, there is no pattern to follow; the chaotic sequence distribution is close to uniform or high entropy distribution, which is difficult to statistically fit.

[0075] In summary, the present invention not only has good chaotic characteristics and system stability in mathematics, but also has the comprehensive advantages of high security, high synchronization, and high adjustability in practical applications. It is the key technical element for this scheme to achieve lightweight, high-intensity encrypted transmission, and provides a high-quality dynamic security foundation for subsequent steps.

[0076] Step 102: Determine a pre-processed data block according to the mouse original data segmentation result and the dynamic key sequence.

[0077] In some embodiments, step 102 may include:

[0078] Map the original data block according to the mapping coefficient matrix to construct the original data linear mapping item;

[0079] Constructing the chaotic disturbance weighted term according to the chaotic weight factor and chaotic sequence value;

[0080] The pre-processed data block is obtained according to the original data linear mapping item and the chaotic disturbance weighting item.

[0081] Among them, the preprocessing data block is expressed as:

[0082] D(i)=β·M(i)+γ·x(i)mod256

[0083] Where D(i) is the preprocessed data block, M(i) is the original data block, x(i) is the i-th chaotic sequence value, β is the mapping coefficient matrix, and γ is the chaotic weight factor.

[0084] In practice, this formula is used to preprocess and perturb the raw data block M(i) of a wireless mouse. This aims to tightly combine the raw data with the chaotic key sequence before encoding and encryption, achieving initial data obfuscation and enhanced security. By introducing two control coefficients, β and γ, the formula achieves a weighted fusion of the data block and the chaotic sequence. The result is then modulo 256 (within a byte range) to ensure that the output data still conforms to the standard byte format for data transmission.

[0085] D(i) represents the perturbed secure data unit used for subsequent encoding. M(i) represents the i-th data unit captured by the mouse, the original unencrypted data. x(i) corresponds to the i-th chaotic key, derived from the dynamic key generation formula. β is a weight parameter that determines the proportion of the original data in the perturbation. γ controls the influence of the chaotic sequence on the data perturbation.

[0086] β·M(i) is the linear mapping term for the raw data. It scales the original mouse data block M(i) by a factor of β, adjusting the data amplitude and distribution. This term maintains the data's fundamental information characteristics while reserving mixing space for chaotic perturbations. Adjusting β allows the system to balance data accuracy and perturbation strength at different security levels. This term maintains the essential information of the raw mouse data, preserving its structure and statistical properties through linear mapping. This serves as the foundation for subsequent action recognition and response. Choosing a reasonable β ensures that the data can still be decoded and restored after perturbation.

[0087] γ·x(i) is the chaotic perturbation weighting term. The dynamic chaotic key sequence value x(i) is adjusted by the weight γ and then injected into the data. This way, each data block is subjected to a unique and unpredictable dynamic perturbation. γ controls the amplitude of the chaotic perturbation, determining the trade-off between data security and recoverability. Introducing the perturbation of the dynamic chaotic sequence increases the randomness and complexity of the data, significantly enhancing the system's resistance to eavesdropping and tampering attacks. Due to the initial value sensitivity and time dependence of the chaotic sequence, this perturbation is extremely difficult to predict and reproduce.

[0088] The (mod256) modulo operation ensures data formatting. By applying a modulo 256 calculation to the weighted sum, D(i) remains a single-byte value, complying with the wireless mouse transmission protocol. The modulo operation also prevents overflow and illegal encoding, ensuring system compatibility and stability. This ensures data format compliance and transmission protocol compatibility, and is a necessary step in the data preprocessing process to prevent overflow errors during subsequent encoding.

[0089] As can be understood, this formula, by incorporating a dynamic chaotic sequence, achieves a preliminary encryption perturbation of the mouse's raw data, significantly enhancing the data's concealment and protection level, preventing easy data restoration during transmission. The chaotic perturbation term ensures that each data block is perturbed by a different key value at different time points, making it difficult for attackers to recover the true data through packet analysis, replay, or statistical inference. The use of modulo-256 operations ensures that the preprocessed data still conforms to the standard wireless mouse transmission format, eliminating the need for additional encoding conversion and simplifying system design and implementation. The two parameters β and γ provide an interface for adjusting the perturbation ratio, allowing users or the system to dynamically adjust it based on security requirements to achieve the optimal balance between security and transmission performance. The perturbed preprocessed data block D(i) possesses excellent randomness and security properties, providing a solid foundation for subsequent Polar code-based encoding and chaotic phase modulation encryption.

[0090] In summary, this invention achieves effective data preprocessing and encryption perturbation through a linearly weighted combination of raw data and a dynamic chaotic key, followed by modular operations. This significantly enhances data security and attack resistance while maintaining the integrity of the data structure, providing crucial technical support and core support for the secure and reliable transmission of wireless mouse data.

[0091] Step 103: Dynamically generate a channel polarization matrix according to the chaotic sequence value.

[0092] In some embodiments, step 103 may include:

[0093] The basic polarization kernel matrix is processed based on the Kronecker product to obtain the processed recursive expansion term;

[0094] Get the rotation matrix of the chaotic sequence value of the nth iteration;

[0095] The channel polarization matrix is generated according to the recursive expansion term and the rotation matrix.

[0096] Among them, the channel polarization matrix can be expressed as:

[0097]

[0098] Where W(n) is the channel polarization matrix, G is the basic polarization kernel matrix, and n is the polarization order. is the Kronecker product, and R(x(n)) is the rotation matrix.

[0099] In the specific implementation, this formula is used to dynamically generate the channel polarization matrix W(n), which is the core matrix structure of the channel coding scheme based on Polar code. By expanding the proposed method, a high-dimensional polarization matrix is constructed. Combined with the rotation matrix R(x(n)) generated by the chaotic sequence value x(n), the channel polarization matrix based on dynamic modulation of the chaotic sequence is realized, which enhances the flexibility and security of the coding.

[0100] Specifically, W(n) represents the dynamic polarization coding matrix, which is used for channel polarization coding. G represents the Polar code core matrix, which is generally n determines the dimension of the polarization matrix, and 2^n is the matrix size. Represents the recursive expansion of the basic kernel matrix into a high-dimensional polarization matrix. R(x(n)) represents the dynamic rotation matrix, which modulates the polarization matrix based on the chaotic value to enhance the chaotic perturbation.

[0101] is a recursive expansion of the basic polarization matrix. The Kronecker product is a special product of matrices that gradually expands the 2×2 basic polarization kernel matrix to 2 n ×2 n Polarization matrix; this matrix construction is the mathematical foundation for Polar codes to achieve channel polarization, dividing the channel into reliable and unreliable sub-channels. The larger the n, the longer the coding block length, the more pronounced the polarization effect, and the better the coding performance. This matrix, the core of Polar codes, constructed using the recursive Kronecker product, effectively achieves channel polarization, separates reliable and unreliable channels, and improves coding efficiency and bit error rate performance, making it a highly advantageous channel coding technology in modern communications.

[0102] R(x(n)) is a rotational transformation matrix closely related to the chaotic sequence x(n). It dynamically perturbs the polarization matrix. Through rotational matrix modulation, the polarization matrix acquires time-variability and nonlinear characteristics, enhancing system security. The rotation angle and direction are determined by the chaotic sequence value x(n), ensuring synchronization between the rotation matrix and the key for secure communication. The introduction of dynamic rotational transformation increases the temporal and spatial variability of the polarization matrix, making the encoding process not only a mathematical polarization but also a secure chaotic perturbation layer, preventing attacks based on analysis of a fixed polarization matrix.

[0103] W(n) combines fixed-structure polarization coding with dynamic chaotic perturbations, providing an efficient and secure coding matrix, which is a key technical guarantee for secure data transmission.

[0104] This formula modulates the rotation matrix through a chaotic sequence, dynamically changing the polarization matrix. This prevents attackers from exploiting the fixed matrix structure for cryptanalysis, effectively enhancing data security. The rotation matrix can be dynamically adjusted based on the chaotic sequence to adapt to varying channel conditions and noise environments, improving the anti-interference performance and decoding success rate of the polar code. The rotation perturbation ensures that the encoding matrix is unique for each transmission, preventing replay attacks and the decoding of intercepted data, ensuring the confidentiality and integrity of wireless mouse data. The introduction of chaotic perturbation without compromising the original theoretical framework and performance advantages of Polar codes balances security and efficiency, facilitating integration into existing wireless communication chips and systems.

[0105] In summary, this invention combines the polarization matrix of classic Polar codes with a dynamic rotation matrix based on chaotic sequences to construct a dynamic and secure polarization matrix. This technological innovation not only retains the excellent channel polarization and error correction capabilities of Polar codes, but also significantly improves the security and anti-attack capabilities of wireless mouse data transmission through chaotic perturbations, becoming a highly valuable technical module in this solution.

[0106] Step 104: Calculate the allocation priority of each bit position using a balancing factor according to the channel capacity characteristics and data priority index of the channel polarization matrix.

[0107] In some embodiments, step 104 may include:

[0108] Process the sub-channel capacity according to the balance factor to construct the channel capacity term;

[0109] Constructing a data importance item according to the balance factor and the data importance indicator;

[0110] The allocation priority is determined according to the channel capacity item and the data importance item.

[0111] Among them, the allocation priority can be expressed as:

[0112] P(i)=λ·H(W(i))+(1―λ)·S(i)

[0113] Where P(i) is the allocation priority of the i-th bit in the Polar code, λ is the balancing factor, H(W(i)) is the subchannel capacity, S(i) is the data importance index, and i is the bit index.

[0114] In practice, this formula dynamically calculates the allocation priority P(i) of the i-th bit in the Polar code. This is combined with the polarized subchannel capacity H(W(i)) and the importance index S(i) of the original data information, weighted by a balancing factor λ to achieve a scheduling strategy that jointly optimizes security and data value. This mechanism not only considers the reliability of the channel itself (a core feature of Polar codes) but also incorporates the priority of the original data blocks, ensuring that important information is transmitted preferentially on reliable subchannels, improving overall system efficiency and security.

[0115] P(i) represents the scheduling weight of the i-th bit during the encoding process; higher values give it higher priority. λ controls the weighting relationship between the polarization channel capacity and the importance of the data. H(W(i)) represents the reliability metric for the i-th polarization subchannel; a larger value indicates a lower bit error rate. S(i) represents the priority assessment of the i-th bit in the original data, which is defined according to the task settings. i is the bit index, representing the position index of the coded bit in the Polar code, where N = 2. n .

[0116] λ·H(W(i)) is the channel capacity term. Polar codes divide the transmission channel into reliable and unreliable subchannels based on channel polarization. H(W(i)) measures the reliability of the i-th subchannel; a larger value indicates a lower bit error rate. When λ approaches 1, bit allocation prioritizes channel reliability. This term ensures a high transmission success rate at the communication level. This improves robustness in noisy environments, ensures that coded bits are transmitted over the optimal channel, and reduces bit errors. It also effectively utilizes the polarization characteristics of Polar codes to enhance error correction capabilities.

[0117] (1-λ)·S(i) represents the data importance term. Some data (e.g., mouse control commands and click events) is more critical than other data (e.g., mouse position trajectory). S(i) reflects these differences and is set or learned based on task requirements. When (1-λ) approaches 1, the system prioritizes the transmission of important data over highly reliable channels. This term enables semantic-level scheduling of data at the application layer. This implements a data-level differentiated encoding strategy; critical events (e.g., mouse clicks) are prioritized during transmission. Task-priority-based scheduling meets the needs of modern intelligent applications.

[0118] λ can be dynamically adjusted based on network status: increasing the weight of S(i) under good links and prioritizing H(W(i)) under weak network conditions; adapting to different business models (high-security scenarios vs. high-interactive response scenarios); and providing full-link adaptation from "channel-driven" to "content-driven."

[0119] After taking the weighted sum of the two, P(i) comprehensively reflects the balance between the reliability of the transmission environment and the value of the data itself. It is used to select "frozen bits" and "information bits" in the subsequent Polar code. The larger the value, the more preferred the position is for data carrying, rather than padding or skipping.

[0120] This formula breaks away from the traditional Polar code's "channel-only" frozen bit selection approach and introduces a data-layer priority metric, strongly linking the coding scheduling strategy to data content. This significantly improves the semantic accuracy and scenario adaptability of transmission tasks. Important data is prioritized for reliable channels, increasing the transmission rate and decoding accuracy of high-value data. This is particularly suitable for human-computer interaction applications such as wireless mice and AR / VR control signals. The ability to adjust λ enables the system to quickly shift to a "channel-driven" approach in the face of channel mutations or attacks, and to a "content-driven" approach in stable environments, enhancing the system's self-regulation and steady-state maintenance capabilities. Priority allocation based on content identification facilitates hierarchical management of encryption strategies. For example, by combining the strength of downstream chaotic modulation parameters, hierarchical encryption design can be achieved.

[0121] In summary, this invention constructs a priority scoring function that integrates channel reliability and data value as the key scheduling mechanism for the Polar encoding process. This function not only improves transmission efficiency and information security, but also strengthens the system's ability to perceive task priorities. This is a key support for promoting the "high security, low latency, and strong adaptability" transmission goals for wireless mouse data.

[0122] Step 105: Perform polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimpose chaotic phase modulation to generate an encrypted signal.

[0123] In some embodiments, step 105 may include:

[0124] Performing Polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority to construct a coding item;

[0125] Perform chaotic phase modulation on the chaotic sequence to construct encryption terms;

[0126] The encrypted signal is generated according to the encoding item and the encryption item.

[0127] Among them, the encrypted signal can be expressed as:

[0128] C=F(D,W,P)·exp(j·θ(x))

[0129] Where c is the encrypted signal, F(D,W,P) is the Polar coding function, D is the preprocessed data block, W is the channel polarization matrix, P is the bit allocation priority, j is the imaginary unit, θ(x) is the chaotic phase modulation function, and x is the chaotic sequence.

[0130] In practice, this formula is used to implement joint encoding and encryption of data before transmission. Preprocessed data D, the dynamic channel polarization matrix W, and the bit allocation priority P are input into the Polar coding function F to generate a preliminary encoding result. This data is then modulated and encrypted using a chaotic sequence-controlled phase modulation function exp(j·θ(x)), outputting the final encrypted signal C in the complex domain. This process, which combines source coding (Polar codes) with physical layer encryption (chaotic modulation), is the core implementation of the "encoding-encryption integration" approach of this solution, significantly improving data confidentiality and anti-attack capabilities.

[0131] C represents the encrypted polarization-coded signal, which is the wireless data frame to be transmitted. F(D, W, P) encodes the data block D using the polarization matrix W and the priority P to generate a structured coding codeword. D is the data segment processed by the front-end mapping function, the original data to be encoded. W is the dynamically generated polarization structure that controls the encoding rules. P controls whether each data bit participates in the information bit mapping. j is used to construct the complex signal (modulation). θ(x), a phase function controlled by the chaotic sequence x, determines the modulation angle. x controls the dynamic changes in the modulation function to achieve the encryption effect.

[0132] F(D, W, P) is the encoding term. It executes the Polar code encoding process, mapping the input data D to the polarization structure determined by W. Information bits and frozen bits are selected based on the bit priority P, ensuring that critical data is allocated to reliable subchannels. Matrix operations are used during the encoding process to merge and copy serial and parallel data. The output is a quasi-random, error-resistant codeword sequence, providing data error correction and structural protection for information bits. This achieves structured redundant encoding of data, effectively utilizing channel polarization characteristics to enhance error correction capabilities, and collaborates with the priority mechanism to ensure the reliability of critical data bits.

[0133] exp(j·θ(x)) is the encryption term, which controls the signal's phase rotation based on a set of dynamic phase angles θ(x) generated by the chaotic sequence x. Phase modulation is achieved using the complex exponential form: exp(j·θ) = cos(θ) + j·sin(θ). Each encoded bit symbol is multiplied by a "rotation angle," disrupting its original waveform. Because θ(x) is generated by a chaotic sequence, the modulation pattern is highly unpredictable and difficult to recover by an attacker. This provides dynamic encryption at the physical layer to prevent eavesdropping and replay attacks. Nonlinear perturbations are introduced to create a strong physical encryption barrier. Chaotic driving makes the phase modulation highly dynamic and non-reproducible, compensating for the physical layer exposure risks of traditional encryption algorithms.

[0134] C is the complex domain signal C obtained by multiplying the results of the two processing modules (dot product). It has the following characteristics: it retains the Polar code structure to facilitate subsequent SCL decoding; increases the signal's unpredictability in the time and frequency domains; and effectively improves confidentiality and anti-interference during data transmission. The integration of encoding and encryption avoids the resource waste and synchronization mismatches associated with "two-step" system designs; maintains signal format consistency to facilitate back-end synchronization, decoding, and restoration; and enhances anti-attack capabilities while balancing transmission efficiency and decoding complexity.

[0135] This part implements an integrated architecture of encoding and encryption, avoiding redundant operations in the traditional "encode first, then encrypt" architecture, reducing processing delays and resource consumption, and is suitable for application scenarios that are highly sensitive to delays, such as wireless mice.

[0136] Providing full-link dynamic physical layer security, chaotic phase modulation has inherent uncertainty, making it difficult for attackers to decipher data through statistical analysis even if they intercept it. At the same time, the coding structure enhances anti-interference performance and achieves simultaneous protection of signal-level encryption and error correction.

[0137] Enhance the personalized protection capability for important data, combine the bit allocation priority mechanism in the previous step, ensure that the key data blocks are reasonably positioned in the coding structure and have sufficient modulation intensity, and improve the coupling efficiency of the overall system's security and fault tolerance.

[0138] It adapts to frequency conversion, frequency hopping and channel disturbances in complex wireless environments, uses complex domain signal structure and phase disturbance design, and naturally adapts to anti-interference mechanisms such as frequency hopping and spread spectrum. It is an effective technical means to resist channel degradation, interference injection, data replay attacks, etc.

[0139] In summary, this invention achieves a deep fusion of data structure encoding and physical-layer chaotic encryption, serving as the core of a lightweight, fast, and secure wireless mouse data transmission system. By deeply embedding chaotic modulation within the encoding process, a full-link security architecture is constructed that integrates channel polarization, bit optimization, and physical encryption. This significantly improves the system's anti-interference capabilities, encryption strength, and coding efficiency, a key innovation that distinguishes this invention from existing technologies.

[0140] Step 106: perform phase demodulation on the received encrypted signal according to the synchronized chaotic sequence, and use the reconstructed polarization matrix to restore the original data through a list decoding algorithm to obtain a reconstructed data block.

[0141] In some embodiments, step 106 may include:

[0142] Performing exponential processing on the phase demodulation function of the chaotic sequence to obtain an exponential phase demodulation function, and processing the encrypted signal based on the exponential phase demodulation function to construct a phase demodulation term;

[0143] Processing the phase demodulation term using the reconstructed polarization matrix to construct a polarization decoding term;

[0144] The polarization decoding items are used to restore original data through a list decoding algorithm to obtain the reconstructed data block.

[0145] Among them, the reconstructed data block can be expressed as:

[0146] D′=SCL(C·exp(―j·θ(x′)),W′,L)

[0147] Where D′ is the reconstructed data block, C is the encrypted signal, θ(x′) is the demodulation phase function, x′ is the synchronized chaotic sequence, W′ is the polarization matrix, L is the number of SCL decoding paths, exp(―j·θ(x′)) is the exponential phase demodulation function, and SCL is the successive cancellation list decoding function.

[0148] In the specific implementation, this formula describes the decryption and reconstruction process of the wireless mouse data at the receiving end, which is the last step of this solution. After the data reaches the receiving end, the corresponding chaotic phase sequence θ(x ′ ), inverse phase modulates (i.e., decrypts) the received encrypted signal C, then inputs it into the Successive Cancellation List (SCL) decoding algorithm for Polar decoding, restoring the original preprocessed data block D′. This formula completes the entire process from complex encrypted coded signals to final digital data restoration, ensuring stable and accurate data decryption and recovery in high-security, high-error environments.

[0149] D′ is the original data recovered by the receiving end, which is expected to be equivalent to D at the transmitting end. C is the signal output by the transmitting end after Poly encoding and chaotic modulation. ′ ) is based on the synchronized chaotic sequence x ′ The generated phase value. x ′ The receiver iterates the sequence synchronously using the same initial values and parameters. The polarization matrix W′ reconstructed by the receiver should be identical or dual to the W at the transmitter. L controls the number of polar decoding branches, determining decoding accuracy and complexity. exp(―j·θ(x′)) is conjugated with the transmitter's modulation function to achieve an inverse phase transform. SCL is a polar code decoding method that performs multipath estimation and cancellation.

[0150] C·exp(―j·θ(x′)) is the phase demodulation term, which restores the phase of the received complex domain encrypted signal; exp(―j·θ) is the conjugate complex number of the transmitter modulation function, satisfying: exp(j·θ)·exp(―j·θ)=1; the premise is that the receiver can obtain the same θ(x′) as the transmitter through the synchronization of the chaotic system. ′ ); after demodulation, the encoded data (Polar codeword) is obtained, but it has not yet been decoded. Decryption is completed at the physical layer to restore the encoded data before modulation. The inverse modulation operation is performed to ensure that the encrypted signal transmitted in the wireless channel can be restored by the receiver. Chaotic sequence synchronization must be ensured. Before demodulation, phase perturbations mask the Polar structure, improving physical layer confidentiality.

[0151] SCL is the polarization decoding term. It uses the SCL algorithm to decode the demodulated Polar codewords and recover the original data. It uses the W′ polarization matrix as the basis for the channel structure. It uses the L path list for multipath estimation to improve the decoding success rate in low signal-to-noise ratio environments. During decoding, the maximum likelihood path is selected based on the path likelihood, and the most likely bit sequence is constructed bit by bit. The encoded codeword is converted back to the data domain to complete error correction and information reconstruction. The multipath inference mechanism improves the robustness of Polar decoding. The larger L, the closer the performance is to maximum likelihood decoding, but the computational complexity is also greater. SCL is particularly suitable for wireless channels that are susceptible to interference or have high bit error rates. For the low bit rate and high accuracy requirements of mouse data streams, SCL is an excellent choice.

[0152] As you can understand, this component enables end-to-end restoration of encrypted signals, addressing "physical encryption" from a modulation and demodulation perspective and "source restoration" from a polarization decoding perspective, forming a complete and secure data closed loop. This enhances the system's tolerance to channel errors. The SCL algorithm provides robust error correction, effectively recovering the original data even in harsh channel environments or with partial packet loss. It enables a lightweight, highly secure embedded decoding architecture. SCL is suitable for resource-limited receiver devices and is highly compatible with chaotic synchronization mechanisms, making it particularly well-suited for low-power scenarios such as wireless mice and IoT terminals. It ensures strict symmetry with the encryption encoding process, ensuring a one-to-one correspondence between modulation and demodulation, encoding, and decoding, eliminating restoration failures caused by signal mismatches. It effectively protects against various wireless channel threats, including replay attacks, missynchronization attacks, and random injection attacks.

[0153] In summary, the present invention's closed-loop data reception link, through chaotic synchronous phase restoration and continuous elimination decoding, achieves accurate decoding and restoration of encrypted coded composite signals, a crucial step in ensuring system integrity, security, and viability. It not only makes the encryption mechanism reversible but also ensures data accuracy in low-power wireless environments, forming a key pillar supporting the present invention's trusted computing and lightweight communications.

[0154] In some embodiments, the step of dynamically generating a chaotic sequence in the present invention may include:

[0155] The receiving end uses the same bifurcation parameters and time decay coefficient as the sending end;

[0156] Transmitting an encrypted seed of the initial value of the chaotic system through a secure channel;

[0157] The receiving end decrypts according to the encryption seed and synchronously executes the chaotic sequence generation process with the same number of iterations.

[0158] Specifically, to ensure that the chaotic system can correctly reproduce the sender's dynamic key sequence at the receiver, the receiver must use the same control parameters as the sender. μ is the bifurcation control parameter in the logistic map, which determines the nonlinear strength and chaotic behavior of the chaotic system; α is the time decay factor, which controls the exponential decay of the chaotic sequence. Only when these two parameters are consistent can the iterative sequence be consistent under the same initial value.

[0159] Because the chaotic sequence is highly dependent on the initial value x(0), the scheme uses a secure channel (for example, using a public key encryption mechanism) to send the initial value or its encrypted form (seed) from the sender to the receiver. This ensures that even if the communication is monitored, the attacker cannot directly obtain the initial value and thus cannot reproduce the chaotic key sequence.

[0160] After receiving the encrypted seed, the receiver uses the corresponding private key or pre-shared key to decrypt it and restore the original initial value x(0); then, the receiver uses the known parameters μ and α to calculate the following formula:

[0161] x(n+1)=μ·x(n)·(1―x(n))·exp(―αt)

[0162] The same number of iterations as the transmitter is performed to gradually generate the chaotic key sequence {x(1), x(2), ..., x(N)}. This sequence will be used in multiple core steps such as decryption, polarization matrix construction, and signal restoration to achieve timing synchronization, key synchronization, and data consistency restoration.

[0163] Through the above three steps, the receiving end can achieve precise synchronization of the chaotic system, ensuring that the subsequent demodulation, decoding and data reconstruction processes are completely consistent with the sending end, thereby completing data communication reliably and securely.

[0164] See also Figure 2 , Figure 2 Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. Figure 2 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0165] According to the preset bifurcation parameters, initial values and time decay coefficients, a dynamic key sequence is generated through the iterative Logistic mapping chaotic system.

[0166] Determine a pre-processed data block according to the mouse original data block result and the dynamic key sequence;

[0167] Dynamically generate channel polarization matrix according to chaotic sequence values;

[0168] Calculating the allocation priority of each bit position using a balancing factor according to the channel capacity characteristics and data priority index of the channel polarization matrix;

[0169] Performing polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal;

[0170] The received encrypted signal is phase-demodulated according to the synchronized chaotic sequence, and the original data is restored by using a list decoding algorithm using a reconstructed polarization matrix to obtain a reconstructed data block.

[0171] See also Figure 3 , Figure 3Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 3 As shown, this embodiment provides a computer-readable storage medium 500 on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0172] According to the preset bifurcation parameters, initial values and time decay coefficients, a dynamic key sequence is generated through the iterative Logistic mapping chaotic system.

[0173] Determine a pre-processed data block according to the mouse original data block result and the dynamic key sequence;

[0174] Dynamically generate channel polarization matrix according to chaotic sequence values;

[0175] Calculating the allocation priority of each bit position using a balancing factor according to the channel capacity characteristics and data priority index of the channel polarization matrix;

[0176] Performing polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal;

[0177] The received encrypted signal is phase-demodulated according to the synchronized chaotic sequence, and the original data is restored by using a list decoding algorithm using a reconstructed polarization matrix to obtain a reconstructed data block.

[0178] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0179] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0180] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices, and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or boxes.

[0181] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system that is implemented in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0182] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0183] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0184] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A wireless mouse data security transmission method based on Polar code and chaotic encryption, characterized in that: include: According to the preset bifurcation parameters, initial values and time decay coefficients, a dynamic key sequence is generated through the iterative Logistic mapping chaotic system. Determine a pre-processed data block according to the mouse original data block result and the dynamic key sequence; Dynamically generate channel polarization matrix according to chaotic sequence values; Calculating the allocation priority of each bit position using a balancing factor according to the channel capacity characteristics and data priority index of the channel polarization matrix; Performing polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal; The received encrypted signal is phase-demodulated according to the synchronized chaotic sequence, and the original data is restored by using a list decoding algorithm using a reconstructed polarization matrix to obtain a reconstructed data block.

2. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 1, characterized in that: The method of iteratively generating a dynamic key sequence through a Logistic mapping chaotic system according to a preset bifurcation parameter, an initial value, and a time decay coefficient includes: Get the current state value representing the state of the chaotic system at each iteration; Constructing a Logistic chaos term according to the bifurcation parameter and the current state value; Construct an exponential decay modulation term based on the time decay coefficient and the system time variable; The dynamic key sequence is iteratively generated according to the Logistic chaos term and the exponential decay modulation term.

3. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 2, characterized in that: The dynamic key sequence is expressed as: x(n+1)=μ·x(n)·(1―x(n))·exp(―αt) Where x(n+1) is the dynamic key sequence, x(n) is the current state value, μ is the bifurcation parameter, α is the time decay coefficient, and t is the system time variable.

4. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 3, characterized in that: The method of determining the pre-processed data block according to the mouse original data segmentation result and the dynamic key sequence includes: Map the original data block according to the mapping coefficient matrix to construct the original data linear mapping item; Constructing the chaotic disturbance weighted term according to the chaotic weight factor and chaotic sequence value; The pre-processed data block is obtained according to the original data linear mapping item and the chaotic disturbance weighting item.

5. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 4, characterized in that: The pre-processed data block is represented as: D(i)=β·M(i)+γ·x(i)mod256 Where D(i) is the preprocessed data block, M(i) is the original data block, x(i) is the i-th chaotic sequence value, β is the mapping coefficient matrix, and γ is the chaotic weight factor.

6. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 5, characterized in that: The dynamically generating a channel polarization matrix according to the chaotic sequence value includes: The basic polarization kernel matrix is processed based on the Kronecker product to obtain the processed recursive expansion term; Get the rotation matrix of the chaotic sequence value of the nth iteration; The channel polarization matrix is generated according to the recursive expansion term and the rotation matrix.

7. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 6, characterized in that: The allocation priority of each bit position is calculated by the balance factor according to the channel capacity characteristics and data priority index of the channel polarization matrix Process the sub-channel capacity according to the balance factor to construct the channel capacity term; Constructing a data importance item according to the balance factor and the data importance indicator; The allocation priority is determined according to the channel capacity item and the data importance item.

8. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 7, characterized in that: The performing polar encoding according to the pre-processed data block, the channel polarization matrix, and the allocation priority, and superimposing chaotic phase modulation to generate an encrypted signal, includes: Performing Polar coding according to the preprocessed data block, the channel polarization matrix, and the allocation priority to construct a coding item; Perform chaotic phase modulation on the chaotic sequence to construct encryption terms; The encrypted signal is generated according to the encoding item and the encryption item.

9. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 8, characterized in that: Phase demodulation is performed on the received encrypted signal according to the synchronized chaotic sequence, and the original data is restored by using a list decoding algorithm using a reconstructed polarization matrix to obtain a reconstructed data block, including: Performing exponential processing on the phase demodulation function of the chaotic sequence to obtain an exponential phase demodulation function, and processing the encrypted signal based on the exponential phase demodulation function to construct a phase demodulation term; Processing the phase demodulation term using the reconstructed polarization matrix to construct a polarization decoding term; The polarization decoding items are used to restore original data through a list decoding algorithm to obtain the reconstructed data block.

10. The method for secure wireless mouse data transmission based on Polar code and chaotic encryption according to claim 9, characterized in that: The step of dynamically generating the chaotic sequence includes: The receiving end uses the same bifurcation parameters and time decay coefficient as the sending end; Transmitting an encrypted seed of the initial value of the chaotic system through a secure channel; The receiving end decrypts according to the encryption seed and synchronously executes the chaotic sequence generation process with the same number of iterations.

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