Mimicry encryption method and system for communication data transmission

Abstract

The invention relates to the technical field of communication data security, and discloses a mimicry encryption method and system for communication data transmission. The method comprises the following steps: synchronizing a high-precision timestamp through an NTP protocol and generating a standardized environment parameter; temperature, voltage and signal strength indexes are extracted based on the environmental parameters, entropy hybrid calculation and dynamic splicing coding are carried out, and a dynamic encryption key is generated; performing multi-layer mimicry permutation and diffusion confusion on plaintext data after the plaintext data is partitioned by using the key to generate a final ciphertext; performing protocol encapsulation and transmission optimization on the ciphertext; and the receiving end realizes decryption through de-encapsulation and inverse mimicry transformation, and dynamically adjusts the key in combination with environmental parameter feedback. According to the method, key dynamics is enhanced through environment randomness, multi-layer encryption and integrity verification are combined, the anti-attack ability and safety of data transmission are remarkably improved, and the method is suitable for communication scenes with high real-time performance requirements.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication data security technology, and in particular to a quasi-state encryption method and system for communication data transmission. BACKGROUND

[0002] In the field of communication data security technology, the existing scheme usually generates static keys and uses fixed encryption algorithms, which has the limitations of key vulnerability, insufficient encryption strength, and low transmission security. The existing methods rely on preset keys and standard encryption protocols, which are prone to key leakage and encryption failure in dynamic environment changes and real-time communication conditions, making it difficult to meet the stable implementation of communication data transmission security. To address the problem of how to generate dynamic and random keys based on environmental entropy sequences and reference timestamps through dynamic concatenation encoding and SHA-3 one-way hash processing in communication data transmission, the existing technology generally has common shortcomings in the dynamic and random aspects of key generation, making it difficult to form a consistent process of key generation-encryption-transmission in real-time communication environments, resulting in insufficient key updates and encryption reliability. SUMMARY

[0003] The present application provides a quasi-state encryption method and system for communication data transmission to solve the problem of how to generate dynamic and random keys based on environmental entropy sequences and reference timestamps through dynamic concatenation encoding and SHA-3 one-way hash processing in communication data transmission.

[0004] To solve the above technical problems, the present application provides a quasi-state encryption method for communication data transmission, comprising: Obtain a network clock signal, perform NTP protocol multi-round timestamp exchange and clock deviation compensation, execute environmental sensor data acquisition and multi-source denoising processing, generate high-precision reference timestamp, original environmental parameter and standardized environmental parameter structure; the reference timestamp is initiated by a system clock module to send a synchronization request and receive time response data from an NTP server; the environmental sensor includes a temperature sensor, a voltage detection unit and a wireless signal strength acquisition device; the environmental sensor is triggered by a hardware interrupt or a timer; the original environmental parameter includes a timestamp identifier, a sensor type, a sampling value and a sampling state marker field; Extract temperature, voltage and signal strength indicators from the standardized environmental parameters, perform entropy value mixing calculation, dynamic concatenation encoding and SHA-3 one-way hash processing, and generate a dynamic encryption key structure; Receive the dynamic encryption key and plaintext data, perform data block processing, use the current round key to perform multi-layer quasi-state permutation and multi-round diffusion confusion, and generate a final ciphertext structure; The final ciphertext is subjected to multi-layer encapsulation based on TCP / IP protocol to generate a transmission data packet, perform a packet header check code integrity verification, and mark a QoS priority to generate an optimized transmission packet; The received remote transmission data packet is subjected to protocol decapsulation processing, combined with integrity verification, to realize decryption key synchronization, perform inverse quasi-state transformation processing, and generate a decrypted plaintext structure; The decrypted plaintext and the original plaintext are compared bit by bit, and a key update instruction is generated based on a failure event analysis. The environment quality feedback parameter is generated by combining the sliding window statistics of the standardized environment parameters.

[0005] Further, the temperature, voltage, and signal strength indicators are extracted from the standardized environment parameters, and the process of entropy value hybrid calculation includes: The temperature, voltage, and signal strength indicators are independently extracted by the environment data analysis module; According to the time sequence order, each indicator is synchronously read through the preset analysis rule and data mapping table; The temperature, voltage, and signal strength indicators are respectively input into the entropy value calculation unit. The unit adopts an entropy value hybrid calculation method based on information entropy theory. For each indicator, the probability distribution function is calculated, and the change frequency and amplitude in the predefined time window are statistically analyzed to obtain the single entropy value; The entropy value hybrid calculation synthesizes the single entropy values of each indicator according to the dynamic weight coefficient through a weighted fusion strategy. The weight coefficient is dynamically adjusted based on the historical stability and current fluctuation amplitude of the indicator; The entropy value hybrid calculation process includes an abnormality detection link. If the input indicator has abnormal fluctuations or data missing, the system compensates through redundant sensor data and records detailed information in the abnormal event log.

[0006] Further, the process of dynamic splicing encoding specifically includes: The environment entropy sequence is divided into multiple time segments using a dynamic window sliding mechanism, and each segment is accurately positioned according to the time point of the reference timestamp; The reference timestamp and the environment entropy sequence are dynamically spliced and encoded on the time axis. The splicing and encoding process includes binary expansion of the timestamp information and bit-level mapping of the environment entropy sequence values. The mapping adopts a nonlinear encoding algorithm to enhance the complexity and unpredictability of the encoding result; The nonlinear encoding algorithm combines the high and low bits of the timestamp and the dynamic weight of the environment entropy sequence to generate a binary sequence of the initial key material; The implementation of dynamic splicing and encoding also considers the compensation of network transmission delay, and adjusts the timestamp offset to realize the time sequence consistency of the initial key material.

[0007] Further, the process of generating the dynamic encryption key structure specifically includes: The initial key material is formatted, including data padding and block division; The absorption and squeezing operations of multiple iterations are performed to achieve high-strength cryptographic hash calculation using the Keccak sponge structure; The hash result generates a dynamic encryption key structure, which contains a fixed-length key data field and an additional random identifier, for subsequent key round calling of the quasi-algorithm encryption module.

[0008] Further, receiving the dynamic encryption key and plaintext data, the process of data block processing specifically includes: According to the preset block size parameter, the continuous plaintext data is divided into a plurality of standard data block sequences; The buffer mechanism is adopted, combined with the sliding window technology, to realize the integrity and continuity of the data block, and to support the padding processing of the last block of data to meet the block size requirement; During the block processing, the system monitors the state of the input data stream, detects abnormal data length or format error, and records the abnormal event in the system log, and triggers the corresponding error recovery mechanism.

[0009] Further, the process of using the current round key to perform multi-layer quasi-state permutation and multi-round diffusion confusion specifically includes: According to the current encryption round counter, the corresponding current round key is dynamically located and extracted, and the key rotation mechanism is adopted, combined with the key index and time stamp synchronization information, to realize the timing accuracy and unpredictability of key calling; The quasi-state permutation operation is based on the permutation table and mapping rule driven by the dynamic key, and performs multi-dimensional permutation on the input data block sequence at the byte level and the bit level; The permutation operation adopts a pipeline processing structure, supports parallel computing to improve processing efficiency, and has an embedded exception detection mechanism to monitor the data integrity and calculation accuracy in real time.

[0010] Further, the process of generating the final ciphertext structure specifically includes: The diffusion mechanism based on the permutation-substitution network is adopted to uniformize the bit distribution of the intermediate ciphertext and eliminate the statistical correlation between data; The diffusion process combines the key-related diffusion matrix and dynamic parameters to realize data confusion through nonlinear function mapping; The confusion processing dynamically generates a confusion mask by introducing a pseudo-random sequence generator combined with a key-derived seed value, and performs a bitwise XOR operation on the diffusion data to realize random disturbance of the data; The confusion mechanism supports multi-level and multi-mode switching, and can dynamically adjust the confusion strength and mode according to the security situation feedback.

[0011] Further, the process of generating the dynamic encryption key structure further comprises: First, the environment parameters corresponding to the millisecond timestamp are extracted by the time series alignment module; Among them, is the entropy value of the first class index, is the probability distribution of the th sampling value in the time window, is the total number of samples, is the normalized environment parameter sampling value; Further, dynamic weight fusion is performed:

[0012] In the formula, is the environment entropy sequence, is the weight coefficient; Further, the time sequence is aligned by the dynamic window sliding mechanism, and the nonlinear mapping of splicing encoding is defined: Among them, is the binary encoding of the th time slice, is the XOR operation, is the low 32-bit value of the reference timestamp, represents the right shift operation, : down rounding; The initial key material is input into the SHA-3 module, and a 512-bit hash operation is performed through the Keccak sponge structure to generate a 256-bit dynamic encryption key.

[0013] Further, the process of generating the final ciphertext structure further comprises: Extract the round key from the dynamic encryption key, and define the quasi-state permutation operation: Among them, is the th block of intermediate ciphertext, is the permutation function based on the round key , is the plaintext data block, is the current round key, is the random permutation factor, is the bitwise XOR operation; Further, the diffusion confusion of the intermediate ciphertext is performed, and the diffusion matrix operation of the SPN network is defined: wherein, is the diffusion data, is the key-derived 8x8 matrix, is the intermediate ciphertext, block, is the bias vector; Further, the confusion mask generation is defined as:

[0014] wherein, is the confusion mask of the block, PRG is a pseudo-random sequence generator, is the current round key, is a modulo operation.

[0015] Further, a quasi-state encryption system for communication data transmission is applied to any of the above methods, comprising: a quasi-state encryption module for obtaining installation parameters and completing the definition; a data acquisition unit for acquiring communication data before encryption and outputting a standard communication data packet; a clock synchronization module for acquiring a system clock synchronization signal and generating a decryption time reference; a parameter matching unit for receiving a standard communication data packet and a local environment parameter fingerprint, performing matching processing and outputting a matching result; a reverse quasi-state transformation module for accepting a decryption key seed, performing reverse quasi-state transformation to generate an original plaintext data block; a control execution unit for receiving a control signal and completing data transmission control; a record updating unit for recording abnormal information and updating decryption parameters.

[0016] The key innovations of the present application include: (1) By extracting temperature, voltage, signal strength indicators from standardized environmental parameters for entropy value mixing calculation, an environmental entropy sequence is generated, and then based on the sequence and the reference timestamp, dynamic splicing coding is performed to generate initial key materials.

[0017] (2) The initial key materials are subjected to SHA-3 one-way hash processing to generate a dynamic encryption key structure, ensuring that the key has high dynamicity and randomness in the communication process.

[0018] (3) The current round key is extracted from the dynamic encryption key, quasi-state permutation operation is performed, and diffusion confusion processing is performed on the intermediate ciphertext to generate the final ciphertext structure, so as to improve the security of the encryption process.

[0019] The main beneficial effects are as follows: (1) Through the implementation of dynamic generation and splicing coding of the environmental entropy sequence, it is ensured that the initial key material has high randomness and dynamics in the generation process, effectively addressing the problem of insufficient dynamicity of key generation in the background technology.

[0020] (2) The use of SHA-3 one-way hash processing makes the dynamic encryption key structure have irreversibility and high security in the key update process, ensuring the encryption reliability in the communication data transmission process.

[0021] (3) The combination of paratopic permutation operation and diffusion confusion processing ensures the security and attack resistance of the final ciphertext structure in the transmission process, which is suitable for high requirements for encryption strength in real-time communication environment. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 A flowchart of a paratopic encryption method for communication data transmission provided by an embodiment of the present application; Figure 2 A structural block diagram of a paratopic encryption system for communication data transmission provided by an embodiment of the present application. DETAILED DESCRIPTION

[0023] Embodiment one: reference Figure 1 is a flowchart of a paratopic encryption method for communication data transmission provided by an embodiment of the present application, which can at least include steps S100-S600: S100, obtain a network clock signal, perform NTP protocol multi-round timestamp exchange and clock deviation compensation, generate a high-precision reference timestamp and a standardized environment parameter structure; S200, extract temperature, voltage, and signal strength indicators from the standardized environment parameters, perform entropy value mixing calculation, dynamic splicing coding, and SHA-3 one-way hash processing, and generate a dynamic encryption key structure; S300, receive the dynamic encryption key and plaintext data, perform data block processing, use the current round key to perform multi-layer paratopic permutation and multi-round diffusion confusion, and generate a final ciphertext structure; S400, perform multi-layer encapsulation based on the TCP / IP protocol on the final ciphertext, generate a transmission data packet, perform packet header checksum integrity verification, and mark the QoS priority to generate an optimized transmission packet; S500, receive the remote transmission data packet, perform protocol decapsulation processing, combine the integrity verification, realize decryption key synchronization, perform inverse paratopic transformation processing, and generate a decrypted plaintext structure; S600, compare the decrypted plaintext and the original plaintext bit by bit, generate a key update instruction based on the failure event analysis, combine the standardized environment parameters for sliding window statistics, and generate an environment quality feedback parameter.

[0024] The step S100 comprises at least steps S110-S130: S110, obtaining a network clock signal, performing NTP protocol synchronization processing to obtain a reference timestamp; The process of obtaining a network clock signal, performing network time protocol (NTP) synchronization processing, and obtaining a reference timestamp is as follows: the reference timestamp is initiated by a system clock module, time response data from an NTP server is received, clock deviation calculation and delay compensation algorithm processing is performed, and a high-precision network synchronization reference timestamp is generated. The synchronization processing includes multiple rounds of timestamp exchange to reduce the influence of network delay fluctuation. Further, the system performs abnormality detection on the received time data, such as timeout and clock drift abnormality, and records abnormal events in the system log for subsequent analysis. The reference timestamp is output as the clock reference input to the subsequent S120 step, ensuring the time synchronization of environmental parameter acquisition and key generation. Through the network clock signal acquisition and NTP protocol synchronization processing, the system realizes high-precision and low-delay acquisition of the reference timestamp, providing an accurate time reference for dynamic key generation.

[0025] S120, extracting millisecond-level precision from the reference timestamp, collecting environmental sensor data, and generating original environmental parameters; The process of extracting millisecond-level precision from the reference timestamp, collecting environmental sensor data, and generating original environmental parameters is as follows: the millisecond-level time information of the reference timestamp is used as a sampling trigger identifier to drive the environmental sensor module to synchronously collect multi-dimensional environmental noise data. The environmental sensor includes but is not limited to a temperature sensor, a voltage detection unit, and a wireless signal strength acquisition device. The sensor is triggered by a hardware interrupt or a timer trigger mechanism to ensure that the sampling time is highly consistent with the reference timestamp. During the collection process, the system performs preliminary filtering on the sensor data to eliminate obvious abnormal values and sensor fault data. The abnormal data is confirmed by a redundant sensor cross-validation mechanism. The collected original environmental parameter data is packaged into a unified data structure, including timestamp identifier, sensor type, sampling value, and sampling state marker fields. The original environmental parameters are output as the parameter input to the S130 step for subsequent multi-source denoising and standardization processing of the environmental parameters. Through the reference timestamp-driven environmental parameter collection, the time synchronization of the environmental noise data and the structured input of the multi-source data are realized.

[0026] S130, performing multi-source denoising processing on the original environmental parameters to generate standardized environmental parameter structures; The process of multi-source denoising processing on the original environment parameters to generate a standardized environment parameter structure is as follows. Specifically, the original environment parameters are first taken as inputs, classified and summarized according to sensor types and sampling time sequences, and multi-source data fusion algorithms are applied to filter noise and verify consistency of multi-sensor data in the same time window. The multi-source denoising processing includes a composite algorithm combining weighted average filtering, Kalman filtering and anomaly detection, and the filtering parameters are adaptively adjusted according to different sensor data characteristics. Further, the system performs normalization processing on the denoised data, maps various environment parameters to a unified numerical range, and forms a standardized environment parameter structure. The structure includes a timestamp identifier, standardized values of various environment parameters and a quality label, and the quality label reflects the integrity and reliability of data acquisition. Abnormal conditions such as data loss or abnormal fluctuations are recorded and trigger a quality feedback mechanism. The standardized environment parameters are taken as output field names and delivered to the generating elements in step S210 for use by the dynamic key generation and update module. Through the multi-source denoising and standardization processing, the system ensures the accuracy and consistency of the environment parameters, and provides a reliable data basis for subsequent entropy calculation and key generation.

[0027] Step S200 includes at least steps S210-S230: S210, extract temperature, voltage and signal strength indicators from the standardized environment parameters, perform entropy value hybrid calculation, and generate an environment entropy sequence; The temperature, voltage, and signal strength indicators are extracted from the standardized environment parameters, and entropy value fusion calculation is performed to generate an environment entropy sequence. Specifically, the standardized environment parameters are input, and the temperature, voltage, and signal strength indicators are independently extracted by the environment data analysis module to ensure that the timestamps corresponding to each indicator are consistent with the structure of the standardized environment parameters. The extraction process synchronously reads each indicator in time sequence order according to the preset analysis rules and data mapping table, avoiding time mismatches caused by data delays or missing. Further, the temperature, voltage, and signal strength indicators are input into the entropy value calculation unit, which uses an entropy value fusion calculation method (EFC) based on information entropy theory. Specifically, for each indicator, its probability distribution function is calculated, and its frequency and amplitude of change within a predefined time window are statistically analyzed to obtain a single entropy value. The entropy value fusion calculation uses a weighted fusion strategy to combine the single entropy values of each indicator according to dynamic weight coefficients, which are dynamically adjusted based on the historical stability and current fluctuation amplitude of the indicators, ensuring that the environment entropy sequence accurately reflects the overall randomness and uncertainty of the environment parameters. This entropy value fusion calculation process includes an anomaly detection step. If the input indicators exhibit abnormal fluctuations or data missing, the system compensates using redundant sensor data and records detailed information in the anomaly event log for subsequent analysis. The environment entropy sequence is output as the field name and passed to the mixed element input of the subsequent S220 step for use by the dynamic key generation and update module, further implementing dynamic adjustment of the key based on environmental randomness. By extracting key indicators from standardized environment parameters and performing entropy value fusion calculation, the system quantifies environmental randomness and provides a high-quality entropy source basis for dynamic key generation.

[0028] S220, based on the environment entropy sequence and the reference timestamp, performing dynamic splicing encoding to generate an initial key material; Based on the environment entropy sequence and the reference timestamp, dynamic splicing encoding is performed to generate the initial key material. Specifically, the environment entropy sequence and the reference timestamp are first received by the key material construction module as input. The module performs time series alignment processing on the environment entropy sequence to ensure synchronization with the millisecond-level time precision of the reference timestamp. Specifically, the system uses a dynamic window sliding mechanism to divide the environment entropy sequence into multiple time segments. Each segment is precisely positioned according to the time point of the reference timestamp to avoid misalignment caused by time drift or network delay. Subsequently, the reference timestamp and the environment entropy sequence are dynamically spliced and encoded on the time axis. The splicing and encoding process includes binary expansion of the timestamp information and bit-level mapping of the environment entropy sequence values. The mapping uses a nonlinear encoding algorithm to enhance the complexity and unpredictability of the encoding results. Specifically, the nonlinear encoding algorithm combines the high and low bits of the timestamp and the dynamic weights of the environment entropy sequence to generate a binary sequence of the initial key material. This process further includes encoding integrity checking. The system performs multiple rounds of checking and verification on the generated initial key material. If an encoding anomaly or checking failure is found, a re-encoding mechanism is triggered and the abnormal event is recorded. The implementation of dynamic splicing encoding also considers the compensation of network transmission delay to ensure the timing consistency of the initial key material. The initial key material is passed to the input of the processing object in step S230 as the output field name for subsequent one-way hash processing. Through the dynamic splicing encoding based on the environment entropy sequence and the reference timestamp, the system realizes the timing synchronization and randomness fusion of the key material, laying a solid foundation for the generation of dynamic encryption keys.

[0029] S230, performing SHA-3 one-way hash processing on the initial key material to generate a dynamic encryption key structure; The initial key material is subjected to SHA-3 one-way hash processing to generate a dynamic encryption key structure. Specifically, the initial key material is input into a hash processing module, which performs one-way hash calculation on the input data using the Secure Hash Algorithm 3 (SHA-3). Specifically, the system first formats the initial key material to ensure that it meets the input specifications of the SHA-3 algorithm, including data padding and block division, and then performs multiple rounds of absorption and squeezing operations using the Keccak sponge structure to achieve high-strength cryptographic hash calculation. The SHA-3 one-way hash processing process ensures the irreversibility and collision resistance of the key material, effectively preventing key reverse derivation or prediction. During the hash calculation process, the system monitors the processing status in real time, and if abnormal input or calculation error is detected, it immediately triggers the error handling mechanism and records the abnormal information in the security log. The hash result generates a dynamic encryption key structure, which contains a fixed-length key data field and an additional random identifier, used for subsequent key round calling in the analog algorithm encryption module. The dynamic encryption key is output as the field name and passed to the encryption key input of S310, ensuring that the encryption process uses the latest and dynamic key. Through the execution of SHA-3 one-way hash processing, the system achieves high-strength security protection of dynamic keys, enhancing the overall security of communication data transmission.

[0030] In another embodiment: In S210, the standardized environmental parameters output by S130 are first input, including temperature, voltage, and signal strength indicators. First, the time series alignment module extracts the environmental parameters corresponding to the millisecond timestamp, and formula ① calculates the single-item entropy value: wherein, is the entropy value of the th indicator, is the probability distribution of the th sampling value within the time window, is the total number of samples, is the standardized environmental parameter sampling value.

[0031] Data source mapping: temperature sensor data → temperature indicator → , voltage detection unit data → voltage indicator → , signal strength data → .

[0032] The three entropy values are dynamically weighted and fused by formula ②:

[0033] wherein, is the environmental entropy sequence, is the weight coefficient, calculated by the index fluctuation amplitude (Equation 2) The output environmental entropy sequence is consumed by the mixing element of step S220.

[0034] Step S220 receives the environmental entropy sequence and the reference timestamp of step S110, and aligns the time sequence through the dynamic window sliding mechanism. Equation 3 defines the nonlinear mapping of splicing coding: wherein, is the binary code of the th time slice, is the XOR operation, is the low 32-bit value of the reference timestamp, represents the right shift operation, : round down.

[0035] Data source mapping: environmental entropy sequence → , timestamp → . The output initial key material is consumed by the processing object of step S230.

[0036] Step S230 inputs the initial key material into the SHA-3 module and performs 512-bit hash operation through the Keccak sponge structure to generate a 256-bit dynamic encryption key. The output dynamic encryption key is consumed by the encryption key of step S310.

[0037] Step S300 at least contains steps S310-S330: S310, receive plaintext data input, perform data block processing, and obtain a standard data block sequence; The system first receives the plaintext data input, which is passed to the module by the upper application or the transmission module. Specifically, the plaintext data enters the data preprocessing unit through the data interface module, and the preprocessing unit performs block processing on the plaintext data. According to the preset block size parameter, the continuous plaintext data is divided into a plurality of standard data block sequences. The data block processing adopts a buffer mechanism combined with a sliding window technology to ensure the integrity and continuity of the data blocks, while supporting padding processing of the last block of data to meet the block size requirement. During the block processing, the system monitors the state of the input data stream, detects abnormal data length or format error, records the abnormal event in the system log, and triggers the corresponding error recovery mechanism. After completing the data block processing, the standard data block sequence is transmitted to the input data of the subsequent S320 step as the output field name, so that the quasi-state algorithm encryption module can obtain a standardized encryption data structure. The data block sequence simultaneously feeds back the current data processing state to the system monitoring module, providing a data basis for subsequent security situation analysis.

[0038] S320, extracting the current round key from the dynamic encryption key, performing multi-layer quasi-state permutation operation to generate intermediate ciphertext; Further, the process of extracting the current round key from the dynamic encryption key, performing multi-layer quasi-state permutation operation to generate intermediate ciphertext is specifically, the dynamic encryption key is input into the key management unit as the input, and the key management unit dynamically locates and extracts the corresponding current round key according to the current encryption round counter. The round key extraction adopts a key rotation mechanism combined with key index and timestamp synchronization information to ensure the timing accuracy and unpredictability of key calling. The extracted current round key is then input into the quasi-state permutation module, which performs multi-layer quasi-state permutation operation. Specifically, the quasi-state permutation operation is based on a dynamic key driven permutation table and mapping rule to perform multi-dimensional permutation of the input data block sequence at the byte level and the bit level. The permutation process combines random permutation factors and key-related parameters to enhance the complexity and irreversibility of the permutation. The permutation operation adopts a pipeline processing structure to support parallel computing to improve processing efficiency, while an abnormality detection mechanism is built in to monitor the data integrity and calculation accuracy in real time during the permutation process. If a permutation abnormality is detected, the system automatically records the abnormal event and starts the rollback mechanism to ensure the stability of the encryption process. The output of the quasi-state permutation operation is the intermediate ciphertext, which is transmitted to the input data of the S330 step as the output field name for subsequent multi-round diffusion confusion processing. Through the current round key extraction and quasi-state permutation operation, the system realizes the high coupling of the key and the data, and improves the security strength and attack resistance of the encryption process.

[0039] S330. Perform multiple rounds of diffusion obfuscation on the intermediate ciphertext to generate the final ciphertext structure; The process of performing multi-round diffusion obfuscation on the intermediate ciphertext to generate the final ciphertext structure is as follows: The intermediate ciphertext is input into the multi-round diffusion obfuscation module. This module first performs a multi-round diffusion algorithm on the intermediate ciphertext, specifically employing a diffusion mechanism based on a Substitution-Permutation Network (SPN) to homogenize the bit distribution of the intermediate ciphertext and eliminate statistical correlations between data. The diffusion process combines a key-related diffusion matrix and dynamic parameters, using nonlinear function mapping to achieve data obfuscation, further enhancing the complexity and anti-analysis capability of the ciphertext. Subsequently, the system performs obfuscation processing on the diffused data. This obfuscation processing introduces a pseudo-random sequence generator, combined with a seed value derived from the key, to dynamically generate an obfuscation mask, and performs a bit-by-bit XOR operation on the diffused data to achieve random perturbation of the data. This obfuscation mechanism supports multi-level and multi-mode switching, and can dynamically adjust the obfuscation strength and mode according to security situation feedback, effectively resisting differential and linear attacks. The multi-round diffusion obfuscation module has a built-in error detection and recovery mechanism to ensure the integrity and correctness of the output data, and abnormal events are recorded in detail in the security log. The result of the multi-round diffusion obfuscation process is output as the final ciphertext structure, with the output field named "Final Ciphertext." This final ciphertext is passed to the transmission data input in step S410 for use by the ciphertext protocol encapsulation transmission module. Through this diffusion obfuscation process, the system achieves deep processing of the intermediate ciphertext, significantly improving the security and anti-cracking capability of data encryption.

[0040] In another embodiment: Step S310 receives plaintext data transmitted from the upper-layer application and divides it into 1024-byte blocks. The data block sequence is buffered using a sliding window mechanism and output to the data to be encrypted in step S320.

[0041] Furthermore, step S320 extracts the round key from the dynamic encryption key, and formula ④ defines the mimicry permutation operation: in, For the intermediate ciphertext piece, For round-based keys The permutation function, For plaintext data blocks, This is the key for the current round. For random permutation factors, This is a bitwise XOR operation.

[0042] Data source mapping: Dynamic encryption key → Data block → The output intermediate ciphertext is consumed by the input data of step S330.

[0043] Furthermore, step S330 performs diffusion obfuscation on the intermediate ciphertext, and formula ⑤ defines the diffusion matrix operation of the SPN network: in, For the data after diffusion, An 8x8 matrix derived from the key. For the intermediate ciphertext piece, This is the bias vector.

[0044] Formula 6 defines the generation of the obfuscation mask:

[0045] in, For the first Block obfuscation mask, PRG is a pseudo-random sequence generator. This is the key for the current round. Modulo operation (remainder operation).

[0046] The final ciphertext is consumed by the transmitted data in step S410.

[0047] The technical effects of this section are as follows: the randomness of the environment is quantified by entropy value mixing calculation, and high-complexity key material is generated by dynamic splicing encoding. The key irreversibility is ensured by SHA-3 processing. The plaintext data is divided into blocks, permuted and diffused to form an attack-resistant ciphertext structure, realizing the dynamic coupling of the encryption process with time sequence and environmental parameters.

[0048] Step S400 includes at least steps S410-S430: S410. Obtain the final ciphertext, perform TCP / IP protocol encapsulation processing, and generate a transmission data packet; As an input, the final ciphertext is first taken over by a protocol encapsulation module, which performs multi-layer encapsulation processing according to the Transmission Control Protocol (TCP) and Internet Protocol (IP) specifications in the transport layer protocol stack. Specifically, the system embeds the final ciphertext in the TCP data payload part, and combines the IP header information to complete the data packet construction. This process includes generating TCP header fields such as source port, destination port, sequence number, acknowledgement number, and control flag bits to ensure the correct routing and transmission order of the data packet in the network. At the same time, the IP layer is responsible for filling in the source address, destination address, and fragmentation control fields to ensure the integrity of the data packet and the accuracy of the transmission path. Further, multi-layer encapsulation based on the TCP / IP protocol is performed. The protocol encapsulation module completes the checksum calculation of the data packet by calling the system underlying network interface to ensure the integrity of the data during transmission. Further, the system performs buffer management on the encapsulated data packet, dynamically adjusts the sending window size and retransmission strategy according to the network conditions, and prevents network congestion and data packet loss. In abnormal cases such as encapsulation failure or checksum error, the system triggers an exception handling mechanism, records error logs and performs a retry operation. The transmission data packet is passed to the receiving data input of the subsequent S510 step as an output field name, ensuring that the receiving end can correctly obtain the complete data packet and achieve data continuity and transmission reliability across modules.

[0049] S420, extracting the packet header check code from the transmission data packet for integrity verification and generating a transmission verification mark; The integrity verification module extracts the packet header check code as input from the transmission data packet, and processes it in detail. Specifically, the system first parses the header information of the transmission data packet, locates the packet header check code field, which contains the checksum defined in the TCP / IP protocol stack, for detecting errors in the transmission process of the data packet. The integrity verification module uses the standard checksum algorithm to recalculate the header and payload of the transmission data packet, and compares the calculation result with the packet header check code. If they are consistent, the system confirms that the data packet integrity is not damaged, and generates a transmission verification mark to indicate that the verification is successful. Otherwise, if the check code does not match, the system determines that the data packet has transmission errors, and immediately triggers the error handling process, including discarding the error data packet, recording error event logs and notifying the upper module for retransmission request. The system supports multiple verification mechanisms, combining Cyclic Redundancy Check (CRC) and TCP checksum to improve the accuracy of error detection. The verification process is monitored in real time to ensure that each transmission data packet is strictly integrity detected. The verification mark is used as an output field name, which is passed to the check element input of the subsequent S520 step, used for integrity state judgment of the decryption key synchronization generation module, to realize cross-module security data flow control.

[0050] S430, performing QoS priority marking processing on the transmission data packet to generate an optimized transmission packet; As input of the transmission data packet, the Quality of Service (QoS) priority marking processing is performed. The optimization transmission structure module first analyzes the service type field and priority identifier of the data packet. Specifically, according to the preset QoS policy rules, the system classifies the transmission data packet into different priority levels, and the priority level is dynamically adjusted by the network management policy, combined with the current network load condition and security situation feedback. The optimization transmission structure module gives higher transmission weight to high-priority data packets, adjusts the queuing order of data packets in the network queue, and delays or limits the bandwidth of low-priority data packets. The processing process uses the Differentiated Services CodePoint (DSCP) marking mechanism to embed the priority information in the service type field of the IP header, and realizes end-to-end service quality guarantee. Further, the system combines the congestion control algorithm to dynamically adjust the transmission rate and retransmission strategy to ensure the timely transmission of critical encrypted data packets. The optimization transmission structure module has built-in monitoring function, which collects performance indicators such as transmission delay, packet loss rate and bandwidth utilization in real time, and adjusts the QoS policy according to the feedback. In abnormal cases such as priority conflict or policy failure, the system automatically records the event and triggers the policy correction process. The optimized transmission packet is output as a field name, which is passed to the network transmission input of step S510 to ensure that the receiving end can receive data according to the optimized priority order, and realize the transmission efficiency and security guarantee across steps.

[0051] Step 500 includes at least steps S510-S530: S510, receive remote transmission data packet, perform protocol encapsulation processing, and get the ciphertext to be decrypted; The transmission data packet received as input by the far end is output by the transmission data packet of the previous step S410, and specifically, the transmission data packet enters the protocol decapsulation processing unit through the network interface module. The protocol decapsulation processing unit first performs protocol level analysis on the transmission data packet, and according to the transmission control protocol (TCP) and internet protocol (IP) specifications, the protocol header information is stripped layer by layer to recover the final ciphertext data embedded therein. This process includes checksum verification, fragmentation reassembly and sequence number confirmation of the IP header field, to ensure the integrity and correct order of the data packet. Subsequently, the TCP layer sorts and retransmits the data packet according to the sequence number and acknowledgement number, and eliminates duplicate or incorrect data packets. The protocol decapsulation processing unit has an exception detection mechanism, which automatically triggers retransmission requests and error log records for abnormal events such as data packet loss, sequence disorder and verification failure, to ensure the reliability and integrity of data transmission. After the protocol decapsulation processing is completed, the obtained plaintext to be decrypted is output as an output field name, which is passed to the decryption input of the subsequent S520 step, to ensure that the receiving end can obtain complete and accurate ciphertext data, and to provide basic data support for decryption key synchronization generation. At the same time, the reception status and abnormal event information of the plaintext to be decrypted are also fed back to the security situation feedback optimization module S600 for subsequent security policy adjustment and key update decision.

[0052] S520, extracting the integrity state from the verification mark, generating the decryption key synchronization, and obtaining the decryption key; The integrity state is extracted from the verification mark as input, which is output by step S420. Specifically, the system first parses the verification result field in the verification mark, which reflects the integrity verification state of the transmission data packet. The integrity verification module determines the validity of the transmission data packet according to the state. If it is determined that the integrity is complete and correct, the system continues to execute the decryption key synchronization generation process; otherwise, if it is determined that the verification fails or the data packet is damaged, the system immediately triggers an error handling mechanism, including discarding the current data packet, recording integrity exception logs, and notifying the upper module to initiate a retransmission request. The decryption key synchronization generation module further receives the environment parameter quality mark from the time synchronization and environment parameter acquisition module S100, and combines the key update instruction of the security situation feedback optimization module S600 to dynamically adjust the key synchronization strategy. Specifically, the system uses a synchronization algorithm to real-time calibrate the dynamic encryption key according to the integrity state and the environment parameter quality mark, to ensure that the decryption key is highly consistent with the encryption end key. The synchronization algorithm combines timestamp alignment, key rotation mechanism and dynamic adjustment of environment entropy sequence to generate the final decryption key through multiple iterations. The process has built-in anomaly detection and recovery function. If the synchronization fails or the key does not match, the system records the decryption failure event and feeds back to the S600 module to trigger key regeneration. The decryption key is output as a field name, which is passed to the key input of the subsequent S530 step to ensure that the inverse quasi-state transformation process uses accurate and synchronized keys, and realizes correct decryption and security verification of data.

[0053] S530, performing inverse quasi-state transformation processing on the to-be-decrypted ciphertext to generate a decrypted plaintext structure; The inverse quasi-state transformation processing module first receives the decryption key output by step S520, combined with the to-be-decrypted ciphertext data. Specifically, the system constructs an inverse transformation mapping table according to the current decryption round key, which is the inverse mapping of the quasi-state permutation operation in the encryption process, ensuring that the data block can be accurately restored. The inverse quasi-state transformation processing adopts a multi-level block inverse permutation algorithm, which performs inverse permutation operation byte by byte and bit by bit for each data block sequence to restore the original data structure. This process combines key-related parameters and dynamic random factors to ensure the uniqueness and unpredictability of the inverse transformation process. The system uses pipeline processing and parallel computing technology to improve processing efficiency, while built-in integrity checking mechanism to monitor the correctness and integrity of the decrypted data in real time. If decryption anomalies or data mismatches are detected, the system automatically records the decryption failure event and feeds back to the security situation feedback optimization module S600, triggering the key update or retransmission mechanism. After the inverse quasi-state transformation is completed, the generated decrypted plaintext structure is output as the field name, which is passed to the verification data input of step S610 for subsequent bit-by-bit comparison and security situation analysis. Through the inverse quasi-state transformation processing, the system realizes efficient and accurate decryption of encrypted data, ensuring the security and integrity of communication data transmission.

[0054] Step S600 includes at least steps S610-S630: S610, obtain the decrypted plaintext and the original plaintext, perform bit-by-bit comparison processing, and generate a decryption accuracy index; Receiving the decrypted plaintext output from the S530 step as input, which is generated by the inverse quasi-order transformation processing module, the system first performs a bit-by-bit comparison between the decrypted plaintext and the original plaintext data. This comparison process is performed by the verification module, which corresponds the decrypted plaintext and the original plaintext one by one according to the data block sequence, and uses a bit-level alignment algorithm to ensure their consistency in time sequence and data structure. The comparison operation is implemented by a hardware acceleration unit or a software instruction set for efficient parallel processing, supporting real-time verification of large-scale data streams. During the comparison process, the system counts the number of correctly matched bits and the total number of bits for each data block, calculates the correctness rate of a single block, and then performs a weighted average of the correctness rates of all data blocks to form the overall decryption correctness rate index. To ensure the accuracy of the comparison, the system introduces an error detection mechanism to identify bit errors caused by transmission noise or decryption anomalies and mark them as error events. The abnormal events are recorded in detail in the security log, including error bit position, timestamp, and related environmental parameters, for subsequent analysis and security situation assessment. This bit-by-bit comparison process continuously monitors in real time under the constraints of system latency and processing capacity, supporting real-time security feedback of data streams. The decryption correctness rate index is output as the field name, which is used as the input basis for the subsequent S620 step of optimization, and is used by the security situation analysis module to realize the closed loop and dynamic adjustment of security performance across modules.

[0055] S620, extract failure event features from the correctness rate index, perform security situation analysis, and generate key update instructions; Further, the failure event features are extracted from the decryption accuracy indicators for security situation analysis, and a key update instruction is generated. Specifically, the system first analyzes the accuracy indicators to identify decryption failure events below a preset threshold. The threshold is dynamically adjusted by the security policy configuration module, combining historical security event data and current network load conditions to ensure the adaptability and sensitivity of the threshold. The security situation analysis module uses multi-dimensional analysis algorithms, including time series anomaly detection, frequency statistics, and pattern recognition, based on failure event features to identify potential attack behaviors or system abnormalities. Specifically, the system aggregates and analyzes failure events through sliding window technology to determine the persistence and severity of the events, and combines environmental parameter quality feedback and transmission performance indicators to comprehensively evaluate the security situation of the current communication link. During the analysis process, the system uses machine learning models or rule engines to classify abnormal patterns, distinguishing between incidental errors and systematic attacks, effectively avoiding false positives. The security situation analysis results trigger the key update strategy, and the system generates a key update instruction based on the strategy. The instruction includes update trigger conditions, update methods, and effective time parameters. The key update instruction is transmitted to the dynamic key generation and update module S200 through an encrypted channel, specifically to the trigger signal input of S210 step, ensuring that the key generation module can respond to security situation changes in a timely manner. The process has built-in exception handling mechanisms. If the key update instruction fails to generate or is transmitted abnormally, the system records error logs and triggers a backup update scheme. The update instruction is transmitted to the trigger signal input of S210 step as an output field name, realizing a closed loop of security policy and dynamic response across modules.

[0056] S630, sliding window statistics are performed on the standardized environmental parameters to generate environmental quality feedback parameters; Further, the process of generating environmental quality feedback parameters through sliding window statistics on the standardized environmental parameters involves the system first receiving standardized environmental parameters from step S130 as input. These parameters include multi-dimensional environmental indicators and quality markers. The environmental quality feedback module employs a sliding window statistical method, setting the window size and sliding step to dynamically cover environmental data within the time series, achieving continuous monitoring. Specifically, the system performs statistical analysis on key environmental indicators such as temperature, voltage, and signal strength, including mean, variance, peak value, and abrupt change detection, to assess the stability and randomness of the environmental data. Quality markers are used as weighting factors to adjust the reliability of the statistical results and remove abnormal or invalid data. During the statistical process, the system combines the environmental entropy sequence and historical quality feedback to construct an environmental quality model, enabling dynamic evaluation of the quality of environmental parameter acquisition. The model uses adaptive thresholds and anomaly detection algorithms to identify noise interference, sensor malfunctions, and data loss during the environmental parameter acquisition process. Upon detecting anomalies, the system triggers a feedback mechanism, feeding back environmental quality feedback parameters to step S130 of the time synchronization and environmental parameter acquisition module S100. These parameters serve as optimization inputs, guiding parameter adjustments for multi-source denoising and sensor calibration. The environmental quality feedback parameters include quality scores, anomaly statistics, and trend analysis results, recorded in detail in the system log for subsequent security situation analysis and key generation optimization. These quality feedback parameters, as output field names, are passed to the optimization input of step S130, achieving cross-module environmental data quality closed-loop and dynamic optimization.

[0057] Example 2: Figure 2 A structural block diagram of a mimicry encryption system for communication data transmission according to an embodiment of the present invention is shown. Figure 2 As shown, the structure may include: The mimicry encryption unit 01 is used to acquire installation parameters and complete installation and constraints. Specifically, it receives installation parameters from an external configuration interface, and under the constraints of the configured parameters, completes the loading of the encryption algorithm, the initialization of the key space, and the constraint of the security policy to form an initial encryption environment. The initial encryption environment is recorded as a configuration file and maintained in a consistent association with the system state. The configuration file is transmitted to the environment parameter acquisition module as initialization parameters, while a log file is retained for subsequent traceability.

[0058] The environment parameter collection module 02 is connected with the quasi-state encryption unit, and is used for collecting standardized environment parameters and performing preprocessing, and outputting an environment parameter sequence. Specifically, initialization parameters output from the quasi-state encryption unit and original environment data collected by a sensor network are received, standardization processing, noise filtering and data smoothing are performed on the original environment data, and an environment parameter sequence is formed according to system configuration; the environment parameter sequence is transmitted to the time synchronization module as a data stream, and corresponding time information is registered in a buffer area for subsequent reading by a data alignment unit.

[0059] The time synchronization module 03 is connected with the environment parameter collection module, and is used for collecting timestamp information and performing verification, and outputting a synchronization time sequence. Specifically, the environment parameter sequence is received from the environment parameter collection module, and time correction and consistency verification are performed in combination with timestamp information provided by a network time protocol server, and a synchronization time sequence is generated when the time synchronization precision requirement is met; the synchronization time sequence is called by the data alignment unit as a time reference, and the corresponding relationship with a synchronization strategy is recorded in a time log.

[0060] The data alignment unit 04 is connected with the time synchronization module and the environment parameter collection module, and is used for performing alignment processing on the environment parameter sequence and the synchronization time sequence, and outputting an aligned time sequence. Specifically, time window division and data alignment are completed based on the synchronization time sequence from the time synchronization module and the environment parameter sequence from the environment parameter collection module, and an aligned time sequence is generated; the aligned time sequence is output to the event determination and arbitration module for calling, and the alignment state is returned to the event log for registration.

[0061] The event determination and arbitration module 05 is connected with the data alignment unit, and is used for performing event determination and arbitration based on a preset threshold table, and outputting a control instruction signal. Specifically, the aligned time sequence from the data alignment unit is received, event feature extraction, determination rule matching and arbitration decision are performed according to the preset threshold table, and a control instruction signal is obtained; the control instruction signal is output to the encryption control module as a trigger condition of the encryption operation, and corresponding event information is recorded in an arbitration log.

[0062] The encryption control module 06 is connected with the event determination and arbitration module, and is used for receiving the control instruction signal and completing encryption operation control. Specifically, the selection of an encryption algorithm and the update of a key are completed based on the control instruction signal from the event determination and arbitration module, and an encryption configuration object is generated; the encryption configuration object is output to an encryption execution interface, and the effective state is returned to the parameter recording and updating unit for registration.

[0063] The parameter recording and updating unit 07 is connected with the encryption control module, and is configured to record the effective time information and update the dynamic key parameters. Specifically, the effective state and the encryption configuration object are received from the encryption control module, the timestamp recording, the key parameter updating and the version management are performed, and the updated key parameters are obtained; the updated key parameters are provided to the quasi-state encryption unit as the key backfilling, and the index relationship consistent with the time sequence is maintained.

Claims

1. A quasi-state encryption method for communication data transmission, characterized in that, The application relates to a high-precision dynamic encryption system based on environmental parameters, which comprises the following steps: A network clock signal is acquired, NTP protocol multi-round timestamp exchange and clock deviation compensation are carried out, environmental sensor data acquisition and multi-source denoising processing are executed, high-precision reference timestamps, original environmental parameters and standardized environmental parameter structures are generated, the reference timestamps are initiated by a system clock module to send a synchronization request and receive time response data from an NTP server, the environmental sensors comprise temperature sensors, voltage detection units and wireless signal strength acquisition devices, the environmental sensors are triggered by a hardware interrupt or a timer trigger mechanism, and the original environmental parameters comprise timestamp identification, sensor types, sampling values and sampling state marker fields; Temperature, voltage and signal strength indicators are extracted from the standardized environmental parameters, entropy value hybrid calculation, dynamic splicing coding and SHA-3 one-way hash processing are carried out, and a dynamic encryption key structure is generated; Dynamic encryption keys and plaintext data are received, data block processing is carried out, multi-layered quasi-state replacement and multi-round diffusion confusion are executed by using current round keys, and a final ciphertext structure is generated; The final ciphertext is subjected to multi-layered encapsulation based on a TCP / IP protocol, a transmission data packet is generated, a packet header check code integrity is verified, a QoS priority is marked, and an optimized transmission packet is generated; Remote transmission data packets are received, protocol encapsulation processing is carried out, integrity verification is combined, decryption key synchronization is realized, inverse quasi-state transformation processing is executed, and a decrypted plaintext structure is generated; The decrypted plaintext and the original plaintext are compared bit by bit, key update instructions are generated based on failure event analysis, and environmental quality feedback parameters are generated by combining the standardized environmental parameters and sliding window statistics.

2. The method of claim 1, wherein the method is used for communication data transmission. The process of entropy value hybrid calculation from the standardized environmental parameters comprises the following steps: Temperature, voltage and signal strength are independently extracted by an environmental data analysis module; According to a time sequence order, each index is synchronously read by a preset analysis rule and a data mapping table; The temperature, voltage and signal strength indexes are respectively input into an entropy value calculation unit, the unit adopts an entropy value hybrid calculation method based on information entropy theory, calculates the probability distribution function of each index, and obtains the single-item entropy value by statistically analyzing the change frequency and amplitude of the index in a predefined time window; The single-item entropy values of the indexes are synthesized according to dynamic weight coefficients by the entropy value hybrid calculation through a weighted fusion strategy, and the weight coefficients are dynamically adjusted based on the historical stability and current fluctuation amplitude of the indexes; The entropy value hybrid calculation process comprises an abnormality detection link, if the input indexes abnormally fluctuate or data is missing, the system compensates by using redundant sensor data, and detailed information is recorded in an abnormal event log.

3. The quasi-state encryption method of communication data transmission according to claim 1, wherein, The process of dynamic splicing coding comprises the following steps: An environmental entropy sequence is divided into multiple time segments by using a dynamic window sliding mechanism, and each segment is accurately positioned according to the time point of the reference timestamp; The reference timestamp and the environmental entropy sequence are dynamically spliced and coded on a time axis, the splicing and coding process comprises binary expansion of the timestamp information and bit-level mapping of the environmental entropy sequence values, the mapping adopts a nonlinear coding algorithm to enhance the complexity and unpredictability of the coding result. The nonlinear encoding algorithm combines the high and low bit interleaving of the timestamp and the dynamic weight of the environmental entropy sequence to generate a binary sequence of the initial key material; The implementation of dynamic splicing encoding also considers the compensation of network transmission delay, and adjusts the time stamp offset to achieve the timing consistency of the initial key material.

4. The quasi-state encryption method of communication data transmission according to claim 1, wherein, The process of generating a dynamic encryption key structure specifically includes: Format processing of the initial key material, including data padding and block division; Performing multiple rounds of absorption and squeezing operations to achieve high-strength cryptographic hash calculation using the Keccak sponge structure; The hash result generates a dynamic encryption key structure, which contains a fixed-length key data field and an additional random identifier for subsequent key round calls in the pseudostate algorithm encryption module.

5. The mimicry encryption method for communication data transmission according to claim 1, characterized in that, The process of receiving dynamic encryption keys and plaintext data for data block processing specifically includes: According to the preset block size parameter, the continuous plaintext data is divided into a plurality of standard data block sequences; Using the buffer mechanism, combined with the sliding window technology, the integrity and continuity of the data block are realized, and the padding processing of the last block of data is supported to meet the block size requirement; During the block processing, the system monitors the state of the input data stream, detects abnormal data length or format error, and records the abnormal event in the system log, and triggers the corresponding error recovery mechanism.

6. The method of claim 1, wherein the method further comprises: The process of using the current round key to perform multi-layer pseudostate permutation and multiple rounds of diffusion confusion specifically includes: According to the current encryption round counter, the corresponding current round key is dynamically located and extracted, and the key rotation mechanism is used to realize the timing accuracy and unpredictability of key calling by combining key index and timestamp synchronization information; The pseudostate permutation operation is based on the permutation table and mapping rule driven by the dynamic key, and performs multi-dimensional permutation on the input data block sequence at the byte level and the bit level; The permutation operation adopts a pipeline processing structure, supports parallel computing to improve processing efficiency, and has an embedded exception detection mechanism to monitor the data integrity and calculation accuracy in real time during the permutation process.

7. The method of quasi-state encryption of communication data transmission according to claim 1, characterized by, The process of generating the final ciphertext structure specifically includes: Using the diffusion mechanism based on the permutation-substitution network, the bit distribution of the intermediate ciphertext is uniformized, and the statistical correlation between the data is eliminated; The diffusion process combines the key-related diffusion matrix and dynamic parameters to realize data confusion through nonlinear function mapping; The confusion processing dynamically generates a confusion mask by introducing a pseudo-random sequence generator and combining a key-derived seed value, and performs a bitwise XOR operation on the diffusion data to realize random disturbance of the data; The confusion mechanism supports multi-level and multi-mode switching, and can dynamically adjust the confusion strength and mode according to the security situation feedback.

8. The quasi-state encryption method of communication data transmission according to claim 1, wherein, The process of generating a dynamic encryption key structure also includes: First, extract the environmental parameters corresponding to the millisecond timestamp through the time series alignment module; ； in, For the first The entropy value of the class indicator, For the first The probability distribution of each sampled value within the time window The total number of samples, Standardized environmental parameter sampling values; Further, dynamically fuse the weights: ； wherein is the environmental entropy sequence, is the weight coefficient; Further, align the timing through the dynamic window sliding mechanism, and define the nonlinear mapping of splicing encoding: ； wherein, is the binary encoding of the time slice, is the XOR operation, is the lower 32 bits of the reference timestamp, denotes a right shift operation, : floor; Input the initial key material into the SHA-3 module, perform 512-bit hash operation through the Keccak sponge structure, and generate a 256-bit dynamic encryption key.

9. The mimicry encryption method for communication data transmission according to claim 1, characterized in that, The process of generating the final ciphertext structure also includes: Extract round key from dynamic encryption key, define pseudo-state permutation operation: ； in, For the intermediate ciphertext piece, For round-based keys The permutation function, For plaintext data blocks, This is the key for the current round. For random permutation factors, This is a bitwise XOR operation; Further, perform diffusion confusion on intermediate ciphertext, define diffusion matrix operation of SPN network: ； wherein, is the post diffusion data, is a key derived 8x8 matrix, is the intermediate ciphertext, block, is the bias vector; Further, define confusion mask generation: ； wherein, is the first block confusion mask, PRG is a pseudo-random sequence generator, is the current round key, is a modulo operation.

10. A quasi-state encryption system for communication data transmission, applied to the method of any one of claims 1-9, characterized in that, Including: Pseudo-state encryption module, for obtaining installation parameters and completing definition; Data acquisition unit, for collecting communication data before encryption and outputting standard communication data packet; Clock synchronization module, for collecting system clock synchronization signal and generating decryption time reference; Parameter matching unit, for receiving standard communication data packet and local environment parameter fingerprint, performing matching processing and outputting matching result; Inverse pseudo-state transformation module, for accepting decryption key seed, performing inverse pseudo-state transformation to generate original plaintext data block; Control execution unit, for receiving control signal and completing data transmission control; Record update unit, for recording abnormal information and updating decryption parameters.

Images