Lithium battery protection board software security communication method, apparatus and device, and medium

Abstract

The invention provides a lithium battery protection board software security communication method and device, equipment and a medium, and the method comprises the steps: S1, obtaining a voltage ripple signal of a lithium battery protection board, carrying out the spectrum analysis of the voltage ripple signal, and generating a ripple feature vector; s2, mapping the ripple feature vector into an intermediate parameter through a Hash algorithm, and decomposing the intermediate parameter to obtain a time slot offset and an interval control factor; s3, based on the ripple feature vector and the interval control factor, performing dynamic disturbance on the standard encryption algorithm to generate a dynamic encryption component, the dynamic encryption component comprising a dynamic S box; and S4, the obtained lithium battery state data is encrypted based on the dynamic encryption component, an encrypted data block is generated, and the sending time sequence of the encrypted data block is determined according to the time slot offset. By adopting the method, fixed correlation characteristics of encryption operation and physical signals can be eliminated, and the capability of resisting side channel attacks in the communication process is improved.

Description

Technical Field

[0001] The present invention belongs to the field of software security communication, and in particular relates to a method, device, equipment and medium for software security communication of a lithium battery protection board. Background Art

[0002] In the development of secure communication technology for lithium-ion battery protection boards, the coordinated design of high-precision voltage monitoring and real-time data encryption has become a key industry trend. Current mainstream solutions typically develop the voltage sampling unit and secure communication unit as independent modules: the voltage sampling portion utilizes high-resolution analog-to-digital conversion technology to accurately acquire battery parameters, while the secure communication portion utilizes a hardware encryption chip to ensure the confidentiality of data transmission. While this modular design achieves physical isolation, it overlooks the interdependencies that arise during system-level operation.

[0003] Because the voltage sampling circuit generates regular current ripples when operating continuously, and the encryption chip has specific power consumption fluctuation cycles when executing algorithms, the two form a composite signal with a timing correlation in the power supply circuit. After an attacker uses a highly sensitive sensor to capture this mixed signal, they can use spectrum analysis and timing matching techniques to isolate the key rhythm information of the encryption operation from the seemingly random physical signal.

[0004] Existing protection measures mainly focus on electromagnetic shielding or algorithm optimization of a single module, but fail to effectively solve the problem of information leakage caused by physical characteristics across modules. This hidden side-channel vulnerability has become a technical bottleneck restricting the development of high-security battery management systems. Summary of the Invention

[0005] Based on this, it is necessary to provide a lithium battery protection board software security communication method, device, equipment and medium to address the above technical problems, which can eliminate the fixed association characteristics between encryption operations and physical signals and improve the communication process's ability to resist side channel attacks.

[0006] In a first aspect, the present application provides a lithium battery protection board software security communication method, comprising:

[0007] S1. Obtain the voltage ripple signal of the lithium battery protection board, perform spectrum analysis on the voltage ripple signal, and generate a ripple feature vector;

[0008] S2. Map the ripple feature vector to an intermediate parameter using a hash algorithm, decompose the intermediate parameter to obtain the time slot offset and interval control factor;

[0009] S3. Based on the ripple eigenvector and the interval control factor, the standard encryption algorithm is dynamically perturbed to generate a dynamic encryption component, which includes a dynamic S-box;

[0010] S4. Encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

[0011] In one embodiment, a voltage ripple signal of a lithium battery protection board is obtained, and a spectrum analysis is performed on the voltage ripple signal to generate a ripple feature vector, including:

[0012] Capturing a voltage ripple signal at a preset sampling rate, wherein the preset sampling rate is determined according to the operating voltage of the lithium battery;

[0013] Perform fast Fourier transform on the voltage ripple signal to extract the spectrum amplitude matrix of the target frequency band;

[0014] Selecting N frequency points with the largest amplitudes from the spectrum amplitude matrix, performing bit width compression processing on the number of each frequency point to generate a compressed frequency point sequence, where N is an integer greater than 1;

[0015] The compressed frequency point sequence is weighted and summed according to the preset weight coefficient to generate the ripple feature vector.

[0016] In one embodiment, the ripple feature vector is mapped to an intermediate parameter by a hash algorithm, and the intermediate parameter is decomposed to obtain a time slot offset and an interval control factor, including:

[0017] Obtain the current battery temperature value of the lithium battery protection board, concatenate the ripple feature vector and the current battery temperature value to generate mixed input data;

[0018] Perform K rounds of hash iterations on the mixed input data to generate intermediate parameters, where K is a preset integer and the initial value of each round of hash operation is obtained by XORing the hash result of the previous round with a specified bit segment of the ripple feature vector;

[0019] Perform a segmented bit mask operation on the first half of the intermediate parameter to generate the time slot offset;

[0020] A nonlinear transformation operation is performed on the second half of the intermediate parameters to generate an interval control factor.

[0021] In one embodiment, a standard encryption algorithm is dynamically perturbed based on a ripple eigenvector and an interval control factor to generate a dynamic encryption component, including:

[0022] The composite disturbance factor is generated based on the ripple eigenvector and the interval control factor using the following formula:

[0023] F mix =((F v &0xFF)⊕(I ratio >>12)

[0024] Among them, F mix is the composite disturbance factor, F v is the ripple feature vector, 0xFF is the hexadecimal mask value, & is the bitwise AND operation, ⊕ represents the XOR operation, I ratio is the interval control factor;

[0025] The intermediate perturbed S-box is obtained by dynamically perturbing each element of the Advanced Encryption Standard S-box based on the composite perturbation factor and the interval control factor using the following formula:

[0026] S'[i]=S std [i]⊕F mix <<(I ratio &0x03)

[0027] Among them, S′[i] is the middle perturbation S-box, i is the S-box index, ⊕ represents the XOR operation, << represents the left shift operation, (I ratio &0x03) means extracting the lowest 2 bits of the interval control factor as the number of shift bits;

[0028] Pseudo-random padding bits are inserted into each element of the intermediate perturbation S-box to obtain a dynamic S-box.

[0029] In one embodiment, the acquired lithium battery status data is encrypted based on a dynamic encryption component to generate an encrypted data block, including:

[0030] The lithium battery status data is pre-processed into blocks to generate multiple data sub-blocks, wherein the length of each data sub-block is determined according to the instantaneous fluctuation amplitude of the current battery load current;

[0031] Based on the dynamic S-box, nonlinear replacement is performed on each data sub-block, and the round key is dynamically interpolated on the replaced data sub-block through the time slot offset to generate a perturbed encrypted sub-block;

[0032] The perturbed encrypted sub-block is input into the timing obfuscation model to generate an obfuscation queue. The timing obfuscation model is used to perform the following operations:

[0033] Construct a dynamic time window based on the time slot offset and battery temperature change rate;

[0034] In the dynamic time window, multi-level sending priority weights are generated according to the real-time working voltage gradient of the lithium battery protection board;

[0035] The perturbed encrypted sub-blocks are asynchronously scheduled and sorted by multi-level sending priority weights to generate a confusion queue;

[0036] A redundant check bit is added to each perturbed encrypted sub-block in the confusion queue, and a dynamic mask diffusion process is performed on the redundant check bits based on the interval control factor to generate an encrypted data block.

[0037] In a second aspect, the present application also provides a lithium battery protection board software security communication device, comprising:

[0038] The feature analysis module is used to obtain the voltage ripple signal of the lithium battery protection board, perform spectrum analysis on the voltage ripple signal, and generate a ripple feature vector;

[0039] The feature decomposition module is used to map the ripple feature vector into intermediate parameters through a hash algorithm, decompose the intermediate parameters, and obtain the time slot offset and interval control factor;

[0040] A dynamic encryption module is used to dynamically perturb the standard encryption algorithm based on the ripple eigenvector and the interval control factor to generate a dynamic encryption component, which includes a dynamic S-box;

[0041] The data encryption module is used to encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

[0042] In a third aspect, the present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned lithium battery protection board software security communication method when executing the computer program.

[0043] In a fourth aspect, the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned lithium battery protection board software security communication method is implemented.

[0044] The above-mentioned lithium battery protection board software security communication method, device, equipment, and medium collect the voltage ripple signal of the lithium battery protection board and extract the ripple feature vector that represents the dynamic characteristics of the power supply circuit through spectrum analysis. The ripple feature vector is mapped to an intermediate parameter through a hash algorithm and decomposed into a time slot offset and an interval control factor, realizing the irreversible conversion of physical signal characteristics into encryption logic parameters. Based on the above parameters, the standard encryption algorithm is dynamically perturbed to generate an encryption component containing a dynamic S-box. The fixed execution mode of the encryption algorithm is destroyed by dynamically adjusting the S-box structure. The dynamic encryption component is used to encrypt the lithium battery status data, and the transmission timing of the encrypted data block is dynamically controlled based on the time slot offset, so that the encryption operation and the voltage ripple signal form a non-fixed correlation in terms of timing characteristics and spectrum distribution. The above-mentioned method eliminates the fixed correlation characteristics between the encryption operation and the physical signal by dynamically perturbing the encryption algorithm. The characteristics of the voltage ripple signal are used to make the correlation between the encryption process and the physical signal dynamic and unpredictable, thereby effectively improving the communication process's resistance to side channel attacks. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 A flowchart of a software security communication method for a lithium battery protection board provided by an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a flow chart of a dynamic encryption method provided by an embodiment of the present invention;

[0048] Figure 3 A schematic structural diagram of a software security communication device for a lithium battery protection board provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0050] First, a brief introduction is given to the terms involved in the embodiments of this application.

[0051] A side-channel attack is a method of stealing sensitive data or encryption keys by analyzing the physical signals or environmental information generated by electronic devices during operation, rather than directly cracking the encryption algorithm itself. This attack exploits unintentional information leaked by devices during encryption and communication operations, such as power consumption fluctuations, electromagnetic radiation, time delays, and temperature changes, and infers the content of internally processed data by analyzing the characteristics of these signals.

[0052] The lithium battery protection board (PBO) is a core component of a lithium battery management system, primarily used to monitor battery status, ensure safe charging and discharging, and extend battery life. By monitoring key parameters such as battery voltage, current, and temperature in real time, it prevents abnormalities such as overcharging, overdischarging, and short circuits. It is widely used in electric vehicles, energy storage devices, consumer electronics, and other fields. As lithium battery applications become increasingly complex, the PBO must not only ensure safe battery operation but also meet advanced requirements such as high-reliability communication and anti-interference capabilities, making it an indispensable component of lithium battery safety protection systems.

[0053] The Advanced Encryption Standard (AES) is an internationally accepted symmetric encryption algorithm that uses a block cipher mechanism to provide high-strength data protection. Its core encryption is achieved through multiple rounds of iterative byte substitution, row shifting, column obfuscation, and key addition operations. The byte substitution phase relies on predefined S-boxes (Substitution-boxes) to perform nonlinear transformations—that is, mapping each input byte to a specific output value using a fixed substitution table. S-boxes are a core component in cryptography used to enhance the security of encryption algorithms. Their function is to perform nonlinear transformations on input data using predefined substitution rules. During the encryption process, S-boxes map fixed-length binary inputs to specific outputs, breaking the linear correlation characteristic of the data and thus enhancing the algorithm's resistance to reverse engineering analysis. This nonlinear characteristic makes the encryption operation difficult to crack through mathematical deduction or pattern matching. In particular, dynamically adjusted S-boxes can effectively mask the regularity of the encryption process when defending against side-channel attacks, providing a fundamental guarantee for secure communications.

[0054] A hash algorithm is a one-way cryptographic function that converts input data of arbitrary length into an output value of fixed length. Its core properties include irreversibility and collision resistance. In information security, hash algorithms verify data integrity by generating a unique digital fingerprint (hash value), ensuring that information has not been tampered with during transmission. In encrypted communications, hash algorithms are commonly used for key derivation, data summary generation, and identity authentication. Their output can be used as a dynamic parameter in the construction of encryption logic, providing fundamental support for resisting data forgery and reverse analysis.

[0055] Based on the above glossary, the implementation environment of the lithium battery protection board software security communication method provided in the embodiments of this application is described. Schematically, the implementation environment includes: a terminal, a battery management system, a sensor, and a processor. The terminal is connected to the battery management system, the sensor, and the processor via network signals; the sensors include, but are not limited to, differential voltage sensors, Hall voltage sensors, oscilloscopes, etc.; the processor can be a central processing unit, a multi-core processor, or an artificial intelligence chip, etc., without limitation here.

[0056] In combination with the above explanations of terms and implementation environment, the application scenarios of the embodiments of this application are explained. The lithium battery protection board software security communication method provided in the embodiments of this application can be applied to, but not limited to, the following scenarios:

[0057] In the complex operating environments of electric vehicles, lithium-ion battery protection boards must monitor battery pack voltage, temperature, and other parameters in real time, and exchange high-frequency data with the vehicle's control system. This solution, through dynamic encryption and binding to voltage ripple characteristics, effectively prevents attackers from obtaining battery health status (such as SOC / SOH) through side-channel analysis or forging control commands. This prevents safety hazards such as battery overcharging and thermal runaway caused by data leaks, providing a fundamental guarantee for vehicle safety.

[0058] The lithium-ion battery packs of large-scale energy storage power stations experience significant voltage fluctuations during charging and discharging, placing their communication systems at risk from remote attacks. This method leverages the inherent physical characteristics of battery operation (such as the ripple spectrum) to dynamically generate encryption parameters. This allows the encryption logic of each communication to be deeply coupled with real-time operating conditions. Even if an attacker intercepts the data packets, reverse engineering the battery's core parameters (such as capacity decay) is difficult, thus protecting the integrity of grid dispatch instructions and the stable operation of the energy storage system.

[0059] In medical equipment, industrial robots, and other applications, lithium batteries serve as both a power source and a data collection node. This technology deeply integrates voltage ripple characteristics into the encryption process, making it impossible for attackers to infer encryption keys based on fixed patterns. This protects the confidentiality of device operating data (such as robotic arm motion trajectories) while also avoiding the risk of emergency shutdowns caused by communication interference, establishing an adaptive protection system for the continuous and safe operation of industrial equipment.

[0060] Illustratively, the lithium battery protection board software security communication method provided in the embodiment of the present application can also be applied to other application scenarios. It is only used as an example here and is not limited to the specific application scenario.

[0061] In an exemplary embodiment, Figure 1As shown, a method for software security communication of a lithium battery protection board is provided. This embodiment uses the method applied to a terminal in the aforementioned implementation environment as an example. It is understandable that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps S1 to S4:

[0062] S1. Obtain the voltage ripple signal of the lithium battery protection board, perform spectrum analysis on the voltage ripple signal, and generate a ripple feature vector.

[0063] Specifically, a high-precision voltage sensor is used to collect the voltage ripple signal at the output of the lithium battery protection board in real time. This sensor can be implemented using, for example, a Hall effect sensor or a differential amplifier to ensure the accuracy and stability of the collected signal. A digital signal processor (DSP) or field programmable gate array (FPGA) is used to perform spectrum analysis on the collected voltage ripple signal, extracting the frequency components and amplitude characteristics of the signal. This generates a ripple feature vector containing multiple eigenvalues, which serves as the basic data for the dynamic perturbation of the subsequent encryption algorithm. This step ensures the accurate collection and effective feature extraction of the original signal, providing a reliable source of starting data for the entire communication method.

[0064] S2. Map the ripple feature vector to an intermediate parameter through a hash algorithm, decompose the intermediate parameter to obtain the time slot offset and interval control factor.

[0065] Specifically, a secure hash algorithm (such as SHA-256 or the national secret SM3) is used to map the ripple feature vector to an intermediate parameter of fixed length. Mathematical decomposition methods, such as singular value decomposition or eigenvalue decomposition, are then used to decompose the intermediate parameters into a time slot offset and an interval control factor. When the lithium battery protection board communicates, the time slot offset will generate different time offset values ​​according to the real-time ripple characteristics and temperature data, so that the interval of each data transmission changes randomly. The interval control factor is another dynamic parameter obtained by decomposition, which is used to adjust the update frequency and disturbance intensity of the core components of the encryption algorithm (such as the S box). This step enhances the irreversibility and anti-collision properties of the data through the hash algorithm, and drives the dynamic generation of the two in real time through physical characteristics (ripple, temperature), forming a double randomized protection, so that the encryption process and communication behavior cannot be predicted or reverse modeled, ensuring the randomness and unpredictability of the encryption process. For example, different hash algorithms can be used to implement this step. In addition to the above-mentioned SHA-256 and SM3, other secure hash algorithms can also be selected according to actual needs, as long as they can meet the requirements of mapping the feature vector to an intermediate parameter.

[0066] S3. Based on the ripple eigenvector and the interval control factor, the standard encryption algorithm is dynamically perturbed to generate a dynamic encryption component, which includes a dynamic S-box.

[0067] Specifically, the initial permutation table of the S-box is changed according to the interval control factor, or the nonlinear mapping relationship in the S-box is dynamically updated according to the eigenvalue of the ripple eigenvector. The generated dynamic encryption component enables the encryption process of the encryption algorithm to change with the change of the input signal, thereby enhancing the flexibility and anti-attack ability of the encryption algorithm. This step solves the predictability problem of traditional encryption algorithms in fixed environments through dynamic perturbations, thereby improving the security of the encryption system. For example, in addition to perturbing the S-box of the AES algorithm, similar dynamic perturbations can also be performed on the corresponding components of other symmetric encryption algorithms (such as DES, SM4, etc.), as long as they can achieve dynamic adjustment of the encryption process based on the input eigenvector and the control factor.

[0068] S4. Encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

[0069] Specifically, the collected lithium battery status data (such as voltage, current, temperature and other information) is input as plain text, and the dynamic encryption component generated by S3 is used to perform encryption operations to obtain an encrypted data block. At the same time, according to the time slot offset obtained by S2, the sending time interval of the encrypted data block in the network is controlled so that it is sent to the receiving device according to an irregular timing. This step effectively prevents attackers from analyzing and cracking communication data through fixed timing or patterns through dynamic encryption and timing control, thereby improving the confidentiality and anti-eavesdropping capabilities of communication. For example, during implementation, different data encryption and transmission protocols can be used to complete this step. For example, in industrial control networks, the Modbus TCP / IP protocol can be used in combination with dynamic encryption for data transmission. In wireless communications, the ZigBee or LoRa protocol can be used to achieve wireless transmission of encrypted data, and the calculation method and application method of the time slot offset can be adjusted according to the network environment and real-time requirements.

[0070] The above-mentioned lithium battery protection board software security communication method collects the voltage ripple signal of the lithium battery protection board and extracts the ripple feature vector that represents the dynamic characteristics of the power supply circuit through spectrum analysis. The ripple feature vector is mapped to an intermediate parameter through a hash algorithm and decomposed into a time slot offset and an interval control factor, realizing the irreversible conversion of physical signal characteristics into encryption logic parameters. Based on the above parameters, the standard encryption algorithm is dynamically perturbed to generate an encryption component containing a dynamic S-box. The fixed execution mode of the encryption algorithm is destroyed by dynamically adjusting the S-box structure. The dynamic encryption component is used to encrypt the lithium battery status data, and the transmission timing of the encrypted data block is dynamically controlled based on the time slot offset, so that the encryption operation and the voltage ripple signal form a non-fixed correlation in terms of timing characteristics and spectrum distribution. The above-mentioned method eliminates the fixed correlation characteristics between the encryption operation and the physical signal by dynamically perturbing the encryption algorithm. The characteristics of the voltage ripple signal are used to make the correlation between the encryption process and the physical signal dynamic and unpredictable, thereby effectively improving the communication process's resistance to side-channel attacks.

[0071] In one embodiment, a voltage ripple signal of a lithium battery protection board is obtained, and a spectrum analysis is performed on the voltage ripple signal to generate a ripple feature vector, including:

[0072] The voltage ripple signal is captured at a preset sampling rate, wherein the preset sampling rate is determined according to the operating voltage of the lithium battery.

[0073] Specifically, the voltage ripple signal is captured at a preset sampling rate, wherein the preset sampling rate is determined according to the operating voltage of the lithium battery. For example, when the operating voltage of the lithium battery is low, a relatively low sampling rate can be selected to save resources; when the operating voltage is high, a higher sampling rate is used to ensure the integrity and accuracy of the signal. The determination of the sampling rate can also refer to the Nyquist sampling theorem to ensure that the highest frequency component in the signal can be restored. Exemplarily, an analog-to-digital converter (ADC) can be used to capture the voltage ripple signal, and the capture of different sampling rates can be achieved by setting the sampling frequency parameters of the ADC. For example, the ADS1220 series high-precision ADC of Texas Instruments (TI) is used, and the sampling rate is adjusted by programming its sampling rate register.

[0074] Perform fast Fourier transform on the voltage ripple signal and extract the spectrum amplitude matrix of the target frequency band.

[0075] Specifically, the collected time-domain voltage ripple signal is converted into a frequency-domain signal through fast Fourier transform, and the spectrum amplitude distribution data within the target frequency band (such as 1kHz-5kHz) is intercepted to generate a matrix containing the amplitude of each frequency point. For example, after using the radix 2-FFT algorithm to decompose the signal in the frequency domain, the low-frequency noise band and ultra-high frequency interference components are filtered out, and the core frequency band amplitude matrix reflecting the dynamic characteristics of the battery is retained. This step effectively separates the key physical feature information in the ripple signal through frequency domain feature extraction, providing a basis for feature quantification.

[0076] N frequency points with the largest amplitudes are selected from the spectrum amplitude matrix, and the bit width of each frequency point number is compressed to generate a compressed frequency point sequence, where N is an integer greater than 1.

[0077] Specifically, the N frequency points with the largest amplitudes are selected from the spectrum amplitude matrix, their frequency point numbers are extracted, and their bit widths are compressed. For example, the frequency point numbers are compressed from 16-bit binary representation to 8 bits, and a compact compressed frequency point sequence is generated by truncating the high-order significant data or performing a hash map. This step reduces the storage and computational overhead of high-frequency point data through feature dimensionality reduction and data compression, while preserving the topological relationship of the frequency point distribution and providing lightweight input for subsequent feature fusion.

[0078] The compressed frequency point sequence is weighted and summed according to the preset weight coefficient to generate the ripple feature vector.

[0079] Specifically, the compressed frequency sequence is weighted and summed according to the preset weight coefficient to generate a ripple feature vector. The preset weight coefficient can be set according to the actual application scenario and experience. For example, for certain applications with high stability requirements, the frequency points in the low frequency band can be given a greater weight; and for applications with high dynamic response requirements, the frequency points in the high frequency band can be given a greater weight. The weighted summation process can be simply implemented through matrix operations. The compressed frequency sequence is multiplied element by element by the weight coefficient vector, and then the sum is obtained to obtain the ripple feature vector. This feature vector can effectively characterize the key features of the voltage ripple signal and provide input data with discrimination and stability for subsequent encryption processing. For example, in actual applications, different weight allocation strategies can be selected, such as linear decrease, nonlinear decrease, or dynamic adjustment of weights according to the results of spectrum analysis to adapt to different signal feature extraction requirements.

[0080] In one embodiment, the ripple feature vector is mapped to an intermediate parameter by a hash algorithm, and the intermediate parameter is decomposed to obtain a time slot offset and an interval control factor, including:

[0081] The current battery temperature value of the lithium battery protection board is obtained, and the ripple feature vector and the current battery temperature value are concatenated to generate mixed input data.

[0082] Specifically, a temperature sensor collects the current battery temperature of the lithium battery protection board in real time. The temperature value and the ripple feature vector are concatenated in byte order to generate multidimensional mixed input data containing physical signals and environmental parameters. For example, the 16-bit binary data of the ripple feature vector and the 8-bit binary data of the temperature value are concatenated to form 24-bit mixed input data. This step enhances the randomness and diversity of the input data by integrating the real-time battery temperature information, providing unpredictable initial conditions for the hash operation and preventing attackers from reversely deducing intermediate parameters from a single physical feature.

[0083] Perform K rounds of hash iterations on the mixed input data to generate intermediate parameters, where K is a preset integer and the initial value of each round of hash operation is obtained by XORing the hash result of the previous round with the specified bit segment of the ripple feature vector.

[0084] Specifically, K rounds of hash iterations are performed on the mixed input data, with the initial value of each round being updated by performing an XOR operation on the previous round's hash output and a specified bit segment of the ripple feature vector. For example, a SHA-3 algorithm is used for three rounds of iterations, with the initial value of each round being generated by XORing the lower 16 bits of the previous round's hash result with the upper 8 bits of the ripple feature vector. This step, through multiple rounds of iteration and a dynamic initial value update mechanism, enhances the collision resistance of the hash output, making intermediate parameters impossible to predict using a fixed input pattern, effectively blocking attackers from reverse-engineering the parameter generation logic.

[0085] Perform a segmented bit mask operation on the first half of the intermediate parameter to generate the slot offset.

[0086] Specifically, the first half of the intermediate parameter is divided into multiple bit segments according to a preset segmentation rule. A mask is applied to each bit segment to extract the valid data bits, and then the valid data bits are combined through logical operations to generate the time slot offset. For example, the first 64 bits of the 128-bit intermediate parameter are divided into four 16-bit segments, each of which is bitwise ANDed with a 0xFF mask and concatenated to form a 32-bit time slot offset. This step uses segmentation masks to filter redundant information and retain key control bits, ensuring that the time slot offset not only reflects changes in physical characteristics but also meets the accuracy requirements of encrypted communication timing scheduling.

[0087] A nonlinear transformation operation is performed on the second half of the intermediate parameters to generate an interval control factor.

[0088] Specifically, the second half of the intermediate parameter is input into a nonlinear transformation function (such as modular exponentiation or chaotic mapping) to generate a control factor for adjusting the interval between encryption operations. For example, a modular operation is used to take the remainder of the second half and superimpose a chaotic sequence perturbation to generate a dynamically changing interval control factor. This step breaks the linear correlation of the second half of the parameter through nonlinear transformation, forming a complex mapping relationship between the interval control factor, the physical signal, and the hash output, preventing attackers from inferring the complete encryption logic by intercepting fragmented parameters.

[0089] In one embodiment, a standard encryption algorithm is dynamically perturbed based on a ripple eigenvector and an interval control factor to generate a dynamic encryption component, including:

[0090] The composite disturbance factor is generated based on the ripple eigenvector and the interval control factor using the following formula:

[0091] F mix =((F v &0xFF)⊕(I ratio >>12)

[0092] Among them, F mix is the composite disturbance factor, F v is the ripple feature vector, 0xFF is the hexadecimal mask value, & is the bitwise AND operation, ⊕ represents the XOR operation, I ratio is the interval control factor.

[0093] Specifically, the ripple feature vector is bitwise ANDed with the hexadecimal mask value 0xFF, the interval control factor is right-shifted, and the two results are XORed to obtain a composite perturbation factor that contains both ripple feature information and interval control information. For example, the ripple feature vector can be a 32-bit integer, and the interval control factor can be a 16-bit integer. The above operation results in an 8-bit composite perturbation factor. This step generates a random and unpredictable composite perturbation factor by fusing physical characteristics with dynamic control parameters, providing dynamic input for subsequent encryption component perturbations.

[0094] The intermediate perturbed S-box is obtained by dynamically perturbing each element of the Advanced Encryption Standard S-box based on the composite perturbation factor and the interval control factor using the following formula:

[0095] S'[i]=S std [i]⊕F mix <<(I ratio &0x03)

[0096] Among them, S′[i] is the middle perturbation S-box, i is the S-box index, ⊕ represents the XOR operation, << represents the left shift operation, (I ratio&0x03) means extracting the lowest 2 bits of the interval control factor as the number of shift bits.

[0097] Specifically, based on the lowest two digits of the composite perturbation factor and the interval control factor, each element of the S-box of the standard AES algorithm is shifted and XORed. For example, the composite perturbation factor is left-shifted by the number of shifts (such as 0-3 bits) determined by the lowest two digits of the interval control factor, and then XORed bit by bit with the corresponding element of the standard S-box to generate an intermediate perturbation S-box. This step breaks the static replacement rule of the standard S-box through dynamic shifting and XOR operations, so that the replacement logic of the S-box changes in real time with the physical characteristics of the battery, eliminating fixed patterns that can be captured by side channels during the encryption process, and improving the anti-attack capability of the encryption algorithm.

[0098] Pseudo-random padding bits are inserted into each element of the intermediate perturbation S-box to obtain a dynamic S-box.

[0099] Specifically, a pseudo-random padding bit is inserted into each element of the intermediate perturbation S-box to obtain a dynamic S-box. The position and number of the inserted pseudo-random padding bits can be determined according to certain rules or algorithms, such as inserting one pseudo-random padding bit between the upper 4 bits and the lower 4 bits of each byte, or inserting two pseudo-random padding bits at the end of each byte; the pseudo-random padding bits can be generated by a pseudo-random number generator, which can be initialized based on a timestamp, battery status, or other dynamic data. This step further enhances the unpredictability and complexity of the S-box by adding additional randomness, making it more difficult for attackers to crack the encryption algorithm by analyzing the structure of the S-box. For example, in practical applications, a linear feedback shift register (LFSR) or a pseudo-random number generator based on chaos theory can be used to generate padding bits, thereby improving the security and reliability of the dynamic S-box.

[0100] like Figure 2 As shown, in one embodiment, the acquired lithium battery status data is encrypted based on the dynamic encryption component to generate an encrypted data block, including:

[0101] S21 . Pre-process the lithium battery status data into blocks to generate multiple data sub-blocks, wherein the length of each data sub-block is determined according to the instantaneous fluctuation amplitude of the current battery load current.

[0102] Specifically, the acquired lithium battery status data is pre-processed in blocks to generate multiple data sub-blocks. The length of each data sub-block is determined based on the instantaneous fluctuation amplitude of the current battery load current. The lithium battery status data includes but is not limited to information such as the battery voltage, current, temperature, and capacity. The instantaneous fluctuation amplitude of the battery load current can be monitored in real time by a current sensor. Based on the monitored fluctuation amplitude, the length of each data sub-block is dynamically adjusted to adapt to different load conditions. For example, when the load current fluctuates greatly, shorter data sub-blocks can be generated to improve the flexibility and real-time performance of the encryption processing. Conversely, when the load current fluctuates less, longer data sub-blocks can be generated to improve encryption efficiency. In terms of implementation method, a sliding window algorithm can be used to dynamically adjust the window size based on the load current fluctuation amplitude, thereby achieving block pre-processing of the data.

[0103] S22. Perform nonlinear replacement on each data sub-block based on the dynamic S-box, and perform round key dynamic interpolation processing on the replaced data sub-block through the time slot offset to generate a disturbed encrypted sub-block.

[0104] Specifically, a dynamic S-box is used to perform nonlinear byte replacement on each data sub-block. Round key interpolation is then performed on the replaced data sub-block based on the time slot offset. For example, in the AES round key addition operation, the time slot offset is used as a dynamic interpolation factor and bitwise XORed with the round key to generate a perturbation key that varies with physical characteristics. This step, through the dual effects of the dynamic S-box and the perturbation key, completely randomizes the encryption results of the same plaintext under different working conditions, blocking pattern analysis attacks based on repeated encryption.

[0105] S23. Input the perturbed encrypted sub-block into the timing obfuscation model to generate an obfuscation queue. The timing obfuscation model is used to perform the following operations:

[0106] S231: Construct a dynamic time window based on the time slot offset and the battery temperature change rate.

[0107] S232. Generate multi-level sending priority weights according to the real-time operating voltage gradient of the lithium battery protection board within the dynamic time window.

[0108] S233. Asynchronously schedule and sort the perturbed encrypted sub-blocks through multi-level sending priority weights to generate a confusion queue.

[0109] Specifically, the timing obfuscation model can construct a dynamic time window using a weighted summation algorithm based on time slot offsets and battery temperature change rates. Within the dynamic time window, a linear mapping algorithm is used to generate multi-level transmission priority weights based on the real-time operating voltage gradient of the lithium battery protection board. The real-time operating voltage gradient is calculated by dividing the difference between the current voltage and the previous voltage by the time interval. Based on the magnitude of the voltage gradient, the gradient is mapped to a preset priority weight range. For example, the voltage gradient is divided into three intervals: high, medium, and low, corresponding to weights of 0.8, 0.5, and 0.2, respectively. For example, the priority weight of each perturbed encrypted sub-block can be quickly determined by searching a predefined mapping table. The perturbed encrypted sub-blocks are asynchronously scheduled and sorted using a priority queue algorithm to generate an obfuscation queue. The priority queue algorithm inserts each sub-block into the queue position corresponding to its transmission priority weight based on its transmission priority weight. For example, a maximum heap structure can be used to implement the priority queue. Sub-blocks with higher weights are positioned closer to the front of the heap and are sent first. Sub-blocks with higher priority weights are placed at the front of the queue, thus achieving asynchronous scheduling and sorting. The above steps disrupt the inherent sending rhythm of encrypted data blocks through the coordinated scheduling of dynamic time windows and priority weights, making it impossible for attackers to infer the correlation between data blocks based on timing patterns.

[0110] S24. Add redundant check bits to each disturbed encrypted sub-block in the confusion queue, and perform dynamic mask diffusion processing on the redundant check bits based on the interval control factor to generate an encrypted data block.

[0111] Specifically, redundant check bits are added to each perturbed encrypted sub-block in the obfuscation queue, and dynamic mask diffusion processing is performed on the check bits based on the spacing control factor. For example, after the check bits are generated using the cyclic redundancy check algorithm, the spacing control factor is XORed and shifted with the check bits to generate diffused redundant data. This step, through dynamic mask diffusion, deeply binds the redundant check bits to the encrypted data, ensuring data transmission integrity while preventing the check bits from being parsed alone as a vulnerability for side-channel analysis.

[0112] In summary, the lithium battery protection board software security communication method provided in the embodiment of the present application obtains the voltage ripple signal of the lithium battery protection board and performs spectrum analysis to generate a ripple feature vector to characterize the key features of the physical signal, thereby introducing dynamic factors for the subsequent encryption process; the ripple feature vector is mapped to an intermediate parameter using a hash algorithm and decomposed to obtain a time slot offset and an interval control factor, and the physical signal characteristics are further converted into time and interval parameters for encryption control; based on the ripple feature vector and the interval control factor, the standard encryption algorithm is dynamically perturbed to generate a dynamic encryption component, including a dynamic S-box, so that the nonlinear transformation of the encryption algorithm has dynamics and uncertainty; based on the dynamic encryption component, the lithium battery status data is encrypted and processed, and the sending timing of the encrypted data block is determined according to the time slot offset. By combining dynamic encryption and timing control, the fixed association between the encrypted data and the physical signal is further broken. The above technical solution integrates the physical signal characteristics into the dynamic adjustment of the encryption algorithm and the data transmission timing control, so that there is no longer a fixed pattern between the encryption operation and the physical signal that can be exploited by attackers. This combination of dynamic encryption and timing control can effectively resist side-channel attacks, improve the security and confidentiality of communications, and provide more reliable protection for the communication of lithium battery protection boards.

[0113] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0114] Based on the same inventive concept, the embodiment of the present application further provides a lithium battery protection board software security communication device 10 for implementing the above-mentioned lithium battery protection board software security communication method. The implementation solution provided by the device is similar to the implementation solution described in the above-mentioned method. Therefore, the specific limitations of one or more embodiments of the lithium battery protection board software security communication device 10 provided below can be found in the above-mentioned limitations of the lithium battery protection board software security communication method, and will not be repeated here.

[0115] In an exemplary embodiment, Figure 3 As shown, a lithium battery protection board software security communication device 10 is provided, comprising:

[0116] The characteristic analysis module 11 is used to obtain the voltage ripple signal of the lithium battery protection board, perform spectrum analysis on the voltage ripple signal, and generate a ripple characteristic vector;

[0117] The feature decomposition module 12 is used to map the ripple feature vector into an intermediate parameter through a hash algorithm, decompose the intermediate parameter, and obtain a time slot offset and an interval control factor;

[0118] A dynamic encryption module 13 is configured to dynamically perturb the standard encryption algorithm based on the ripple eigenvector and the interval control factor to generate a dynamic encryption component, the dynamic encryption component including a dynamic S-box;

[0119] The data encryption module 14 is used to encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

[0120] In one embodiment, the feature analysis module 11 includes:

[0121] The signal capture unit is used to capture the voltage ripple signal at a preset sampling rate, wherein the preset sampling rate is determined according to the operating voltage of the lithium battery.

[0122] The spectrum conversion unit is used to perform fast Fourier transform on the voltage ripple signal and extract the spectrum amplitude matrix of the target frequency band.

[0123] The frequency point screening unit is used to select N frequency points with the largest amplitude from the spectrum amplitude matrix, perform bit width compression processing on the number of each frequency point, and generate a compressed frequency point sequence, where N is an integer greater than 1.

[0124] The ripple feature vector generating unit is used to perform weighted summation on the compressed frequency point sequence according to a preset weight coefficient to generate a ripple feature vector.

[0125] In one embodiment, the feature decomposition module 12 includes:

[0126] The data mixing unit is used to obtain the current battery temperature value of the lithium battery protection board, splice the ripple feature vector and the current battery temperature value, and generate mixed input data.

[0127] The hash iteration unit is used to perform K rounds of hash iteration operations on the mixed input data to generate intermediate parameters, where K is a preset integer and the initial value of each round of hash operation is obtained by the hash result of the previous round or the specified bit segment of the ripple feature vector.

[0128] The time slot offset generating unit is used to perform a segmented bit mask operation on the first half of the intermediate parameter to generate a time slot offset.

[0129] The interval control factor generating unit is used to perform a nonlinear transformation operation on the second half of the intermediate parameter to generate an interval control factor.

[0130] In one embodiment, the dynamic encryption module 13 includes:

[0131] The composite disturbance factor generating unit is used to generate a composite disturbance factor based on the ripple characteristic vector and the interval control factor using the following formula:

[0132] F mix =((F v &0xFF)⊕(I ratio >>12)

[0133] Among them, F mix is the composite disturbance factor, F v is the ripple feature vector, 0xFF is the hexadecimal mask value, & is the bitwise AND operation, ⊕ represents the XOR operation, I ratio is the interval control factor.

[0134] The intermediate perturbation S-box generation unit is configured to dynamically perturb each element of the Advanced Encryption Standard S-box based on the composite perturbation factor and the interval control factor using the following formula to obtain the intermediate perturbation S-box:

[0135] S'[i]=S std [i]⊕F mix <<(I ratio &0x03)

[0136] Among them, S′[i] is the middle perturbation S-box, i is the S-box index, ⊕ represents the XOR operation, << represents the left shift operation, (I ratio &0x03) means extracting the lowest 2 bits of the interval control factor as the number of shift bits.

[0137] The dynamic S-box generation unit is used to insert pseudo-random padding bits into each element of the intermediate perturbation S-box to obtain a dynamic S-box.

[0138] In one embodiment, the data encryption module 14 includes:

[0139] The block pre-processing unit is used to perform block pre-processing on the lithium battery status data to generate multiple data sub-blocks, wherein the length of each data sub-block is determined according to the instantaneous fluctuation amplitude of the current battery load current.

[0140] The round key interpolation unit is used to perform nonlinear replacement on each data sub-block based on the dynamic S-box, and perform round key dynamic interpolation processing on the replaced data sub-block through the time slot offset to generate a perturbed encrypted sub-block.

[0141] The timing obfuscation unit is used to input the perturbed encrypted sub-blocks into the timing obfuscation model to generate an obfuscation queue. The timing obfuscation model is used to perform the following operations:

[0142] Construct a dynamic time window based on the time slot offset and battery temperature change rate;

[0143] In the dynamic time window, multi-level sending priority weights are generated according to the real-time working voltage gradient of the lithium battery protection board;

[0144] The perturbed encrypted sub-blocks are asynchronously scheduled and sorted through multi-level sending priority weights to generate a confusion queue.

[0145] The redundancy processing unit is used to add redundant check bits to each disturbed encrypted sub-block in the confusion queue, and perform dynamic mask diffusion processing on the redundant check bits based on the interval control factor to generate an encrypted data block.

[0146] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the lithium battery protection board software security communication method as described above are implemented.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0148] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely illustrative, wherein the components described as separate parts may or may not be physically separated, and the parts displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the disclosed solution. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0149] The above-described embodiments merely represent several implementation methods of the embodiments of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the concept of the embodiments of the present application, and these modifications and improvements fall within the scope of protection of the embodiments of the present application.

Claims

1. A lithium battery protection board software security communication method, characterized in that: The method comprises: S1. Obtain a voltage ripple signal of a lithium battery protection board, perform spectrum analysis on the voltage ripple signal, and generate a ripple feature vector; S2. Mapping the ripple feature vector to an intermediate parameter using a hash algorithm, and decomposing the intermediate parameter to obtain a time slot offset and an interval control factor; S3. Dynamically perturb the standard encryption algorithm based on the ripple eigenvector and the interval control factor to generate a dynamic encryption component, wherein the dynamic encryption component includes a dynamic S-box; S4. Encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

2. The method according to claim 1, characterized in that The step of obtaining a voltage ripple signal of a lithium battery protection board and performing spectrum analysis on the voltage ripple signal to generate a ripple feature vector includes: Capturing the voltage ripple signal at a preset sampling rate, wherein the preset sampling rate is determined according to the operating voltage of the lithium battery; Performing a fast Fourier transform on the voltage ripple signal to extract a spectrum amplitude matrix of a target frequency band; Selecting N frequency points with the largest amplitudes from the spectrum amplitude matrix, performing bit width compression processing on the number of each frequency point, and generating a compressed frequency point sequence, wherein N is an integer greater than 1; The compressed frequency point sequence is weighted and summed according to a preset weight coefficient to generate the ripple feature vector.

3. The method according to claim 1, characterized in that The method of mapping the ripple feature vector into an intermediate parameter by a hash algorithm and decomposing the intermediate parameter to obtain a time slot offset and an interval control factor includes: Acquire the current battery temperature value of the lithium battery protection board, and perform splicing processing on the ripple feature vector and the current battery temperature value to generate mixed input data; Performing K rounds of hash iterative operations on the mixed input data to generate intermediate parameters, where K is a preset integer and the initial value of each round of hash operation is obtained by XORing the hash result of the previous round with a specified bit segment of the ripple feature vector; Performing a segmented bit mask operation on the first half of the intermediate parameter to generate the time slot offset; A nonlinear transformation operation is performed on the second half of the intermediate parameter to generate the interval control factor.

4. The method according to claim 1, wherein The method of dynamically perturbing a standard encryption algorithm based on the ripple eigenvector and the interval control factor to generate a dynamic encryption component includes: The composite disturbance factor is generated based on the ripple characteristic vector and the interval control factor by the following formula: F mix =((F v &0xFF)⊕(I ratio >>12) Among them, F mix is the composite disturbance factor, F v is the ripple feature vector, 0xFF is the hexadecimal mask value, & is the bitwise AND operation, ⊕ represents the XOR operation, I ratio is the interval control factor; Dynamic perturbation is performed on each element of the Advanced Encryption Standard S-box based on the composite perturbation factor and the interval control factor using the following formula to obtain an intermediate perturbation S-box: S'[i]=S std [i]⊕F mix <<(I ratio &0x03) Wherein, S′[i] is the intermediate perturbation S-box, i is the S-box index, ⊕ represents an XOR operation, << represents a left shift operation, (I ratio &0x03) represents extracting the lowest 2 bits of the interval control factor as the number of shift bits; Inserting pseudo-random padding bits into each element of the intermediate perturbation S-box to obtain the dynamic S-box.

5. The method according to claim 1, wherein The method of encrypting the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block includes: Performing block preprocessing on the lithium battery status data to generate a plurality of data sub-blocks, wherein the length of each data sub-block is determined according to the instantaneous fluctuation amplitude of the current battery load current; Performing nonlinear replacement on each of the data sub-blocks based on the dynamic S-box, and performing round key dynamic interpolation processing on the replaced data sub-blocks using the time slot offset to generate a disturbed encrypted sub-block; The perturbed encrypted sub-block is input into a timing obfuscation model to generate an obfuscation queue. The timing obfuscation model is used to perform the following operations: constructing a dynamic time window based on the time slot offset and the battery temperature change rate; In the dynamic time window, a multi-level transmission priority weight is generated according to the real-time operating voltage gradient of the lithium battery protection board; Performing asynchronous scheduling and sorting on the perturbed encrypted sub-blocks according to the multi-level sending priority weights to generate the confusion queue; A redundant check bit is added to each of the perturbed encrypted sub-blocks in the confusion queue, and a dynamic mask diffusion process is performed on the redundant check bits based on the interval control factor to generate the encrypted data block.

6. A lithium battery protection board software security communication device, characterized in that: The device comprises: A feature analysis module is used to obtain the voltage ripple signal of the lithium battery protection board, and perform spectrum analysis on the voltage ripple signal to generate a ripple feature vector; A feature decomposition module, configured to map the ripple feature vector into intermediate parameters using a hash algorithm, and decompose the intermediate parameters to obtain a time slot offset and an interval control factor; a dynamic encryption module, configured to dynamically perturb a standard encryption algorithm based on the ripple eigenvector and the interval control factor to generate a dynamic encryption component, wherein the dynamic encryption component includes a dynamic S-box; A data encryption module is used to encrypt the acquired lithium battery status data based on the dynamic encryption component to generate an encrypted data block, wherein the sending timing of the encrypted data block is determined according to the time slot offset.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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