A method for dynamic encryption and adaptive adjustment of security level of flight data

Abstract

This invention discloses a dynamic encryption and adaptive security level adjustment method for flight data, specifically relating to the field of data security. It addresses the confidentiality and integrity issues of flight data in unstable network environments. The method employs dynamic encryption and adaptive security adjustment by quantifying the quality of the random seed during the mixing process in real time. If the dispersion decreases, an incremental seed is immediately added to block the transmission of weak random sources. Historical trajectories continuously provide threshold correction, ensuring that the key update rhythm keeps pace with link fluctuations. Relying on structured mixing and real-time source replenishment mechanisms, a new key with sufficient security margin is output. The key material maintains both high dispersion and high independence, avoiding randomness decay caused by packet loss, retransmission, or node out-of-sync. Simultaneously, the security level adjustment logic is deeply coupled with the key generation process, achieving an adaptive balance between encryption strength and computational load. This allows flight data to maintain superior performance in terms of confidentiality, integrity, and real-time performance in complex environments.

Description

Technical Field

[0001] This invention relates to the field of data security, and more specifically, to a method for dynamic encryption and adaptive adjustment of security levels for flight data. Background Technology

[0002] In the dynamic encryption and security level adaptive adjustment process for flight data, the airborne terminal needs to periodically update keys with ground stations, satellite relays, or neighboring nodes to ensure the confidentiality and integrity of flight data under different network environments. This process requires each participating node to simultaneously generate high-entropy random numbers and perform multiple rounds of hybrid operations according to a predefined mixing strategy to construct a new encryption key. Simultaneously, it requires rapid switching of encryption algorithms and key strengths at different security levels to ensure a balance between performance and security requirements.

[0003] However, due to the difficulty in precisely synchronizing the packet loss retransmission mechanism and the key negotiation triggering conditions in unstable link environments, the random numbers generated by some nodes fail to participate in the mixing process evenly, or are reused during retransmission. The entropy distribution of the new key material is severely unbalanced, the randomness is significantly reduced, the encryption strength cannot meet the security level requirements, and it is vulnerable to side-channel attacks such as statistical analysis, resulting in security vulnerabilities in the overall data protection strategy.

[0004] To address the aforementioned problems, a technical solution is provided. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a dynamic encryption and security level adaptive adjustment method for flight data. This method involves real-time quantization of the random seed quality during the mixing process, with incremental seeds added immediately upon a decrease in dispersion to block the transmission of weak random sources. Historical trajectories continuously provide threshold correction, ensuring that the key update rhythm keeps pace with link fluctuations. Relying on structured spinning and real-time source replenishment mechanisms, a new key with sufficient security margin is output. The key material maintains both high dispersion and high independence, avoiding randomness decay caused by packet loss, retransmission, or node desynchronization. Simultaneously, the security level adjustment logic is deeply coupled with the key generation process, achieving an adaptive balance between encryption strength and computational load. This enables flight data to maintain superior performance in confidentiality, integrity, and real-time operation under complex environments, thus solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for dynamic encryption and adaptive adjustment of security level of flight data includes the following steps:

[0008] S1: Synchronously collect the random seeds generated by each node, attach a generation time slot label and quality metric to each random seed, and write it into the seed temporary storage table;

[0009] S2: Check the seed temporary table according to the order of the generated time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence;

[0010] S3: Based on the weight level of participating nodes and the generation time slot, the pure entropy index sequence is subjected to staggered rotation mixing, the intermediate key block is output and the entropy distribution map is drawn simultaneously;

[0011] S4: Real-time evaluation of the randomness of the mixed sequence; when the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map.

[0012] S5: After the entropy distribution graph dispersion meets the requirements, the session key is derived based on the intermediate key block and distributed to each participating node.

[0013] In a preferred embodiment, step S1 includes the following:

[0014] Each participating node synchronously generates a random seed within a predetermined time slot. The time synchronization protocol coordinates all participating nodes to ensure consistent generation time. A generation time slot label and a quality metric are attached to each random seed. The random seed, generation time slot label, and quality metric are written as data units into a seed temporary storage table and stored according to the participating node identifier and time slot sequence number.

[0015] In a preferred embodiment, step S2 includes the following:

[0016] The seed temporary storage table is checked in chronological order based on the generation time slot label. Data units containing random seeds, generation time slot labels, and quality metric values ​​are sorted and grouped according to their respective time slots. For each time slot, duplicate random seeds from the same participating node are detected and removed by retaining the data unit with the highest quality metric value and discarding the rest. Missing random seeds corresponding to nodes that did not submit random seeds in a specific time slot are identified and marked.

[0017] In a preferred embodiment, step S2 further includes the following:

[0018] A clean entropy index sequence is generated by extracting random seeds from the updated seed temporary storage table and arranging them in order of generation time slot labels.

[0019] In a preferred embodiment, step S3 includes the following:

[0020] The weight of each participating node is calculated based on its type, historical performance, and network stability. An intermediate key block is generated using an interleaved rotation mixing technique based on the pure entropy index sequence and the weights of the participating nodes. The entropy distribution map of the intermediate key block is calculated and plotted simultaneously to verify its randomness.

[0021] In a preferred embodiment, step S4 includes the following:

[0022] The randomness of the intermediate key block is evaluated in real time. The rotational mixing equilibrium distance and discrete breadth amplitude are extracted from the entropy distribution map. The distance-amplitude resonance coefficient is obtained by comprehensive analysis using these two indicators and compared with a preset threshold. If the distance-amplitude resonance coefficient is lower than the preset threshold, additional random numbers are requested from high-trust nodes, incorporated into the mixing process, and the entropy distribution map is updated to ensure that the randomness of the intermediate key block meets the encryption requirements.

[0023] In a preferred embodiment, step S4 further includes the following:

[0024] The logic for obtaining the rotational mixing equilibrium distance is as follows: by dividing the entropy value sequence into sub-intervals, the root mean square difference between the local mean and the global mean of each sub-interval is calculated to measure the stationarity of the entropy distribution.

[0025] In a preferred embodiment, step S4 further includes the following:

[0026] The logic for obtaining the discrete breadth amplitude is as follows: calculate the difference between the maximum and minimum values ​​of the entropy value sequence and divide it by the global mean to measure the dispersion and volatility of the entropy value distribution.

[0027] In a preferred embodiment, step S5 includes the following:

[0028] The dispersion of the entropy distribution map is evaluated in real time. The dispersion is quantified by calculating the mean of the entropy value sequence and the absolute deviation of each entropy value from the mean. The randomness of the intermediate key block is verified by comparing it with a preset threshold. The intermediate key block is divided into segments of a predefined length, the sub-block with the highest entropy value is selected and a bitwise XOR operation is performed to generate a preliminary session key, and then a hash function is applied to generate the final session key.

[0029] In a preferred embodiment, step S5 further includes the following:

[0030] The final session key is distributed to all participating nodes through a secure channel, and the dispersion index, entropy sequence, and session key generation metadata are recorded in the entropy history database.

[0031] The technical effects and advantages of the dynamic encryption and adaptive security level adjustment method for flight data of this invention are as follows:

[0032] This invention constructs a progressive chain through time-stamped random seeds, sliding-order verification and purification, directional interleaving mixing, balanced distribution inspection, and bidirectional historical backtracking derivation. The output of each stage is both verified and reshaped in the next stage, forming a space-time interwoven random diffusion system. The quality of the random seed is quantified in real time during the mixing process. Once the dispersion decreases, an incremental seed is immediately added to block the transmission of weak random sources. Historical trajectories continuously provide threshold correction, ensuring that the key update rhythm keeps pace with the chain fluctuations. The entire process does not require centralized weighting. Relying on structured spinning and real-time source replenishment mechanisms, it continuously outputs new keys with sufficient security margins within limited computing power. The key material maintains the dual characteristics of high dispersion and high independence, avoiding randomness decay caused by packet loss, retransmission, or node out-of-sync. At the same time, the security level adjustment logic is deeply coupled with the key generation process, achieving an adaptive balance between encryption strength and computational load. This enables flight data to maintain superior performance in confidentiality, integrity, and real-time operation in complex environments such as high-speed maneuvering and cross-domain switching. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating a method for dynamic encryption and adaptive adjustment of security levels for flight data according to the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Example 1: Figure 1 This invention provides a method for dynamic encryption and adaptive security level adjustment of flight data, comprising:

[0036] S1: Synchronously collect the random seeds generated by each node, attach a generation time slot label and quality metric to each random seed, and write it into the seed temporary storage table;

[0037] S2: Check the seed temporary table according to the order of the generated time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence;

[0038] S3: Based on the weight level of participating nodes and the generation time slot, the pure entropy index sequence is subjected to staggered rotation mixing, the intermediate key block is output and the entropy distribution map is drawn simultaneously;

[0039] S4: Real-time evaluation of the randomness of the mixed sequence; when the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map.

[0040] S5: After the entropy distribution graph dispersion meets the requirements, the session key is derived based on the intermediate key block and distributed to each participating node.

[0041] In modern aviation communications, the security of flight data is paramount. Flight data includes sensitive information such as flight paths, navigation parameters, and communication records. This data needs to interact with multiple nodes during transmission, including airborne terminals, ground stations, satellite relays, and neighboring nodes. Due to the complex environments in which aircraft operate at high speeds and switch between domains, network links often face instability, such as packet loss or retransmission. This can lead to insufficient randomness in the encryption key generation process, thereby reducing the strength of data protection. To address this challenge, this invention proposes a dynamic encryption and adaptive security level adjustment method for flight data. This method ensures the confidentiality, integrity, and real-time performance of data by periodically updating the encryption key and adaptively adjusting the security level according to the network environment. Key updates rely on high-entropy random seeds generated by each node, generating a new key through multiple rounds of hybrid computation. However, if the random seed is not correctly collected or reused due to network problems, the randomness of the new key will decrease, making it vulnerable to side-channel attacks. Therefore, step S1, as the starting point of the entire process, aims to provide high-quality initial material for subsequent steps by synchronously collecting random seeds from each node and attaching key tags, laying the foundation for key generation.

[0042] Step S1 includes the following:

[0043] S1.1, Synchronously collect random seeds:

[0044] Each participating node, including airborne terminals, ground stations, satellite relays, and neighboring nodes, simultaneously generates a random seed within a predetermined time period. This predetermined time period is defined as a time slot, and time slots are arranged sequentially by number. All participating nodes use a unified time synchronization protocol to ensure that the random seed generation process is triggered simultaneously at the beginning of each time slot. Each participating node independently generates a highly random value, called the random seed, at the start of its time slot. The random seed generation process relies on the internal random number generation mechanism of each participating node to ensure sufficient unpredictability. Synchronous collection of random seeds and coordination of the behavior of all participating nodes through the time synchronization protocol ensure that the generation time of the random seeds remains consistent, avoiding time mismatches caused by network transmission delays or clock deviations of participating nodes.

[0045] The purpose of synchronously collecting random seeds is to ensure that all participating nodes generate random seeds within the same time window, thereby maintaining the time coordination of the key update process and avoiding seed processing disorder or security vulnerabilities caused by time misalignment. It effectively prevents differences in random seed generation time caused by network instability and improves the time consistency of input data during key generation.

[0046] S1.2, Attach generation time slot labels:

[0047] A generation time slot tag is attached to each random seed. The generation time slot tag is an identifier for the time slot corresponding to the random seed's generation time, specifically pointing to the sequence number of the time slot in which the random seed was generated. The process of attaching the generation time slot tag is executed immediately after the random seed is generated. Each participating node binds the time slot number to the corresponding random seed, forming a complete data unit containing time information. The attachment of the generation time slot tag ensures that each random seed carries a clear identifier of its generation time, facilitating the subsequent verification and organization of random seeds in chronological order.

[0048] The purpose of attaching generation time slot tags to random seeds is to provide time traceability, enabling the system to identify the generation order of random seeds in subsequent steps and detect duplicates or out-of-order issues caused by network retransmissions or delays, thereby maintaining the time consistency of data processing. Effective management of random seeds through time stamping reduces processing errors caused by time misalignments and provides a reliable time reference for subsequent filtering and mixing operations.

[0049] S1.3, Calculate and attach quality metrics:

[0050] A quality metric is calculated and appended to each random seed to assess its level of randomness. The calculation of the quality metric includes the following steps:

[0051] First, the uniformity of the distribution of 0s and 1s in the bit sequence of the random seed is analyzed to obtain the actual entropy value of the random seed, which reflects the degree of randomness of the information in the random seed. Second, the effective bit length of the random seed is determined, which refers to the number of effective bits remaining after removing duplicate or invalid bits caused by defects in the random number generator. Finally, the ratio of the actual entropy value to the theoretical maximum entropy value is calculated. The theoretical maximum entropy value is the maximum possible entropy value of the random seed under an ideal uniform distribution. This ratio is then multiplied by the base-2 logarithm of the effective bit length to obtain the quality metric. The quality metric is appended numerically to the corresponding random seed data unit.

[0052] The purpose of calculating and attaching quality metrics is to quantify the randomness and effectiveness of random seeds, ensuring that only random seeds that meet high-quality standards are used for key generation, thereby improving the security strength of the key. Quality metrics provide an objective basis for selecting random seeds, eliminating those with insufficient randomness or defects, thus enhancing the resistance of newly generated keys to attacks and ensuring the security of the encryption system.

[0053] S1.4, Write to the seed temporary table:

[0054] The collected random seeds and their related information, including the random seed itself, the generation time slot label, and the quality metric, are written into a structured storage unit called the seed temporary table. The seed temporary table organizes data according to the participating node identifier and time slot sequence number, forming an ordered storage structure. The writing process specifically includes: upon receiving a data unit containing the random seed, generation time slot label, and quality metric, determining the corresponding storage location in the seed temporary table based on the generation time slot label and participating node identifier; if the location is empty, the data unit is written directly; if the location already stores other data units, the quality metrics of the new and old data units are compared, retaining the data unit with the higher quality metric and discarding the data unit with the lower quality metric to avoid interference from duplicate data.

[0055] Step S1 constructs a high-quality and time-consistent set of random seeds through synchronous collection, time-stamping, quality assessment, and structured storage, providing reliable input data for key generation in dynamic encryption of flight data. Synchronous collection ensures the time coordination of random seed generation, attaching generation time-slot tags provides time traceability and sequence management capabilities, the calculation and attachment of quality metrics guarantee the randomness and validity of the random seeds, and writing to the seed temporary storage table creates conditions for orderly data storage and efficient processing. Thus, the quality and consistency of the random seeds are strictly controlled in the initial stage of the key generation process, and the problem of randomness decay in unstable network environments is solved through multi-layered technical means, thereby ensuring the security and stability of the entire encryption system.

[0056] Step S1 has completed the synchronous collection of random seeds generated by each participating node, and attached a generation time slot label and quality metric to each random seed, writing this information into a seed temporary storage table. The data units in the seed temporary storage table provide the basic material for subsequent key generation, containing random seeds, generation time slot labels, and quality metrics. However, due to the instability of the flight data transmission link, such as packet loss or retransmission, duplicate or missing random seeds may appear in the seed temporary storage table, directly affecting the randomness and security of subsequent key generation. Therefore, step S2 needs to process the data units in the seed temporary storage table to generate high-quality input data, providing a reliable foundation for the interleaved rotation hybrid operation in step S3.

[0057] The specific processing logic of step S2 includes three sub-steps: checking the seed temporary table in chronological order, removing duplicate or missing random seeds, and generating a pure entropy index sequence.

[0058] Step S2 includes the following:

[0059] S2.1, Check the seed storage table in chronological order:

[0060] The data units in the seed temporary storage table are sorted and checked according to their generation time slot labels. The seed temporary storage table contains multiple data units, each consisting of a random seed, a generation time slot label, and a quality metric. The process first reads all data units in the seed temporary storage table and sorts them in ascending order of their generation time slot labels, forming a time-ordered set of data units. After sorting, the data units are divided into multiple groups according to their generation time slot labels, each group corresponding to a time slot, containing the random seeds and quality metrics submitted by all participating nodes within that time slot. Next, a duplicate check is performed on the data units within each time slot to check if multiple random seeds are submitted by the same participating node. If multiple data units are found to be submitted by the same participating node in the same time slot, the quality metrics of these data units are compared, and the data unit with the highest quality metric is retained, while the remaining duplicates are removed. Simultaneously, a missing status check is performed on each time slot, verifying the submission status of all participating nodes. If a participating node has not submitted a random seed, its missing status in that time slot is recorded.

[0061] The purpose of checking the seed temporary table in chronological order is to ensure that data processing follows the time sequence of random seed generation, maintains data temporal consistency, and avoids problems such as random seed misordering or duplication caused by network transmission delays or retransmissions. By sorting and checking in chronological order, duplicate and missing random seeds can be detected and processed promptly, improving the traceability and accuracy of data processing.

[0062] S2.2, Remove duplicate or missing random seeds:

[0063] Based on the seed temporary storage table checked in chronological order, the data units are cleaned up by removing duplicate or missing random seeds, ensuring that each participating node retains only one high-quality random seed within each time slot. The specific processing procedure is as follows:

[0064] For multiple data units submitted by the same participating node within each time slot, the quality metrics of these data units are compared. The data unit with the highest quality metric is retained, and the remaining duplicate data units are deleted. For participating nodes that have not submitted a random seed, their random seed is marked as missing, and this record is retained in the seed temporary table. After completing the duplicate removal and missing labeling, an updated seed temporary table is generated, in which the data unit corresponding to each participating node for each time slot is either a unique high-quality data unit or is marked as missing. The updated seed temporary table retains the complete structure of all time slots while ensuring the quality and uniqueness of the data units.

[0065] The purpose of removing duplicate or missing random seeds is to ensure the uniqueness and high quality of the random seeds within each time slot, prevent duplicate data from interfering with the key generation process, and facilitate subsequent analysis and processing by recording missing states. By purifying data units, errors caused by data redundancy or missing data are reduced, improving the reliability and security of the key generation process and ensuring the integrity and consistency of the input data.

[0066] S2.3, Generate the pure entropy index sequence:

[0067] Based on the updated seed temporary table, a pure entropy index sequence is generated. The specific generation process is as follows: Random seeds for all participating nodes within each time slot are extracted from the updated seed temporary table. For participating nodes marked as missing, their random seed values ​​are set to null. Then, the extracted random seeds are arranged in ascending order according to the generation time slot label number to ensure the temporal continuity of the sequence. Finally, the sorted random seeds are organized into a sequence named the pure entropy index sequence. During the generation process, the arrangement of random seeds strictly follows the order of the time slots, and missing random seeds are retained in the sequence as null values ​​to ensure that the sequence length is consistent with the number of time slots.

[0068] The purpose of generating a pure entropy index sequence is to provide high-quality, time-consistent input data for subsequent interleaved rotation hybrid operations, ensuring the randomness and security of the key generation process. By constructing a pure entropy index sequence, the quality and time consistency of the input data are ensured, thereby improving the randomness and attack resistance of the key material.

[0069] Step S2 achieves efficient purification and organization of random seed data through three sub-steps: checking the seed temporary storage table in chronological order, removing duplicate or missing random seeds, and generating a pure entropy index sequence. First, time consistency of the data is established through time sorting and checking. Then, data quality is ensured by removing duplicates and marking missing ones. Finally, high-quality input is provided through sequence generation. The entire process effectively solves the problem of duplicate or missing random seeds caused by link instability, improves the reliability and security of the key generation process, and provides a solid technical guarantee for the implementation of dynamic encryption and adaptive security level adjustment methods for flight data.

[0070] Step S2, based on the seed temporary storage table, checks data units in chronological order, removes duplicate or missing random seeds, and generates a pure entropy index sequence, providing a high-quality, time-consistent set of random seeds for subsequent key generation. However, in the scenario of dynamic encryption of flight data, link instability may lead to uneven quality or imbalanced distribution of random seeds at some nodes. If the pure entropy index sequence is directly used to generate the key, it may not meet the requirements of high randomness and security, and is vulnerable to statistical analysis attacks. Therefore, step S3 needs to further improve the randomness and security of the pure entropy index sequence through specific hybrid techniques, generate intermediate key blocks, and ensure their entropy distribution is balanced, supporting the randomness evaluation in step S4 and the session key derivation in step S5.

[0071] The specific processing logic of step S3 includes three sub-steps: determining the weight level of participating nodes, implementing staggered rotation and mixing, and synchronously drawing the entropy distribution map.

[0072] Step S3 includes the following:

[0073] S3.1, Determine the weight level of participating nodes:

[0074] First, each participating node is assigned a weight to quantify its influence and credibility in the key generation process. The weight is determined based on three factors: node type coefficient, historical performance coefficient, and network stability coefficient. The node type coefficient reflects the node's security level and reliability; for example, the coefficient for airborne terminals is set to 1.0, for ground stations to 0.8, and for satellite relays to 0.9.

[0075] The historical performance coefficient is based on the average quality of random seeds submitted by a node in the past; a higher value indicates a better quality random seed. The network stability coefficient is based on the packet loss rate and latency of the communication link; a higher value indicates better network connection stability.

[0076] The weighting process is as follows: First, calculate the product of the node type coefficient and the historical performance coefficient, the product of the historical performance coefficient and the network stability coefficient, and the product of the network stability coefficient and the node type coefficient. Add these three products together, and then divide the sum by the total of the node type coefficient, historical performance coefficient, and network stability coefficient to obtain the final weight value. This calculation method comprehensively considers the inherent attributes of the node, its historical performance, and the real-time network state, avoiding the dominance of a single factor and ensuring that the weight fully reflects the characteristics of the node.

[0077] The purpose of assigning weights to participating nodes is to give different nodes different influences during the key generation process. This ensures that nodes with high security, excellent performance, and stable networks contribute more to key generation, thereby improving the randomness and security of the keys. Through the weighting mechanism, the reliability, historical performance, and network stability information of nodes can be fully utilized to enhance the adaptability and robustness of the key generation process, ensuring high-quality key materials generated in dynamic network environments.

[0078] S3.2, Implement staggered rotational mixing:

[0079] Based on the pure entropy index sequence and the weights of the participating nodes, an interleaved rotation mixing process is performed to generate an intermediate key block. The specific process includes the following stages:

[0080] First, the pure entropy index sequence is divided into multiple subsequences according to time slots. Each subsequence contains the random seeds of all participating nodes in that time slot. Then, within each time slot, the random seeds are sorted in descending order according to the weight of the participating nodes.

[0081] Next, a rotation operation is performed on the sorted list of random seeds. If the number of random seeds is even, a pair of seeds from the beginning and end of the list is XORed to generate mixed seeds. If the number of random seeds is odd, the seed in the middle of the list is kept unchanged, and the remaining seeds in pairs are XORed to generate mixed seeds.

[0082] Next, the mixed seeds generated by adjacent time slots are interleaved. If the number of mixed seeds in two time slots is equal, the mixed seeds at the corresponding positions are XORed. If the number is not equal, the XOR operation is performed on the corresponding positions based on the time slot with the smaller number, and the excess mixed seeds are left unchanged.

[0083] Finally, the interleaved seeds of all time slots are concatenated according to the time slot order and the seed number to generate the intermediate key block.

[0084] The purpose of implementing staggered rotation mixing is to increase the complexity of the mixing process through weighted sorting and rotation operations, enhance the data correlation between time slots through staggered operations, and ensure that the intermediate key block has high randomness and strong entropy characteristics. This mixing technique can significantly improve the randomness and security of the random seed, reduce the risk of randomness degradation caused by unstable communication links or node data desynchronization, and provide high-quality intermediate material for the generation of subsequent session keys.

[0085] S3.3, Simultaneously plot the entropy distribution map:

[0086] While generating the intermediate key block, its entropy distribution is calculated and plotted to verify randomness. The specific process includes the following stages: First, the intermediate key block is divided into segments of fixed length; then, for each segment, the probability of occurrence of each bit value is calculated, and the entropy value of each segment is calculated based on the Shannon entropy principle, obtained by weighted summation of the probability of occurrence of each bit value; next, a line graph is plotted with the segment number as the horizontal axis and the entropy value of each segment as the vertical axis to show the distribution trend of entropy value as it changes with the segment; simultaneously, an entropy threshold is preset. If the entropy value of a segment is lower than this threshold, the segment is marked as abnormal, and its index is recorded for subsequent processing.

[0087] The purpose of synchronously plotting entropy distribution diagrams is to monitor the randomness of intermediate key blocks in real time, ensuring that they meet high entropy requirements and providing an intuitive basis for subsequent randomness verification and optimization. Through the plotting of entropy distribution diagrams and anomaly detection, segments with insufficient randomness can be identified and addressed in a timely manner, improving the transparency and controllability of the key generation process and ensuring the overall security of the encryption system.

[0088] Step S3, through three sub-steps—determining the weight levels of participating nodes, implementing staggered rotation mixing, and synchronously plotting the entropy distribution map—achieves efficient recombination and enhanced randomness of the pure entropy index sequence. The first sub-step optimizes the contribution ratio of participating nodes through weight allocation; the second sub-step enhances data complexity and randomness through staggered rotation mixing; and the third sub-step verifies and ensures the quality of the intermediate key block through the entropy distribution map. These three closely linked sub-steps collectively ensure that the intermediate key block possesses high randomness and strong security, providing solid technical support for the implementation of dynamic encryption and adaptive security level adjustment methods for flight data.

[0089] Steps S1 to S3 have completed the collection, verification, mixing, and entropy distribution plotting of random seeds, generating intermediate key blocks and initially assessing their randomness, laying the foundation for the subsequent derivation of session keys. In the complex network environment of flight data transmission, each node needs to collaboratively generate high-entropy random numbers to ensure the security of the encryption system. However, due to link instability, packet loss or retransmission may occur, and the random seeds of some nodes may not participate in the mixing evenly, or the entropy distribution plot may show excessive convergence deviation, resulting in insufficient randomness of the intermediate key blocks. Directly using such intermediate key blocks to derive session keys will significantly reduce encryption strength and make the system vulnerable to side-channel attacks. Therefore, step S4 needs to introduce a real-time evaluation and dynamic adjustment mechanism to ensure that the quality of the intermediate key blocks meets security requirements and provides reliable key material for step S5.

[0090] Step S4 includes the following:

[0091] S4.1, Extract the vortex mixing equilibrium distance and discrete broad amplitude:

[0092] Two parameters, the vortex mixing equilibrium distance and the discrete broad amplitude, are extracted to quantify the randomness of the intermediate key block. The vortex mixing equilibrium distance measures the stationarity of the entropy value sequence as the segment number changes in the entropy distribution graph. Its calculation process is as follows: First, the entropy value sequence is divided into multiple sub-intervals. Then, the local mean of each sub-interval and the global mean of the entire entropy value sequence are calculated. Next, the difference between the local mean and the global mean of each sub-interval is calculated, and the squares of all differences are summed. Finally, the square root of the result is taken to obtain the vortex mixing equilibrium distance. The smaller the value, the more stable the entropy distribution.

[0093] Discrete breadth measures the degree of dispersion of an entropy sequence. It is calculated by extracting the maximum and minimum values ​​of the entropy sequence, calculating the difference between them, and then dividing this difference by the global mean to obtain the discrete breadth. The larger the value, the stronger the fluctuation of the entropy.

[0094] The purpose of extracting the spin-mixing equilibrium distance and the discrete broad amplitude is to comprehensively evaluate the randomness quality of intermediate key blocks by quantifying the stationarity and volatility of the entropy distribution. A single indicator cannot fully reflect the characteristics of the entropy distribution, while these two parameters provide complementary information from the dimensions of stationarity and dispersion, respectively. This quantification method can intuitively reflect the overall characteristics and local changes of the entropy distribution, providing accurate and objective evaluation criteria, facilitating subsequent comprehensive analysis and adjustment.

[0095] S4.2, Calculate the amplitude resonance coefficient:

[0096] The distance-amplitude resonance coefficient is calculated based on the vortex-mixing equilibrium distance and the discrete broad amplitude. The calculation process is as follows: First, preset weights are assigned to the vortex-mixing equilibrium distance and the discrete broad amplitude, with the magnitude of the weights reflecting the different importance of stationarity and volatility in the assessment of stochasticity; then, the vortex-mixing equilibrium distance is multiplied by its corresponding weight, and the discrete broad amplitude is multiplied by its corresponding weight, and the sum of the two products is calculated; finally, this sum is divided by the sum of all weights to obtain the distance-amplitude resonance coefficient, which serves as a comprehensive assessment index of stochasticity.

[0097] S4.3, determine and request incremental random numbers:

[0098] A preset threshold is set, and the randomness of the intermediate key block is determined by comparing the amplitude resonance coefficient with the preset threshold. The process is as follows: the calculated amplitude resonance coefficient is compared with the preset threshold. If the amplitude resonance coefficient is lower than the preset threshold, a request is sent to the high-trust node to obtain an incremental random number. After receiving the incremental random number, it is added to the pure entropy index sequence, the intermediate key block is regenerated, and the entropy distribution map is updated. Then, the steps of extracting the spin mixing equilibrium distance and discrete amplitude, and calculating the amplitude resonance coefficient are repeated until the amplitude resonance coefficient reaches or exceeds the preset threshold.

[0099] High-trust nodes are pre-defined, trustworthy nodes in a network. They are specially designated due to their high reliability and trustworthiness and are typically used to ensure the security and stability of the system.

[0100] The purpose of judging and requesting incremental random numbers is to ensure that the randomness of the intermediate key block always meets security requirements through a dynamic adjustment mechanism. When the amplitude resonance coefficient is lower than a preset threshold, it indicates insufficient randomness, requiring the introduction of an external high-quality random source for improvement. This adaptive source supplementation mechanism can respond promptly to situations of insufficient randomness, improving the quality of the intermediate key block by introducing incremental random numbers, thereby enhancing the encryption system's resistance to attacks and its security.

[0101] Step S4, through three sub-steps—extracting the spin-mixing equilibrium distance and discrete broad amplitude, calculating the distance-amplitude resonance coefficient, and determining and requesting incremental random numbers—achieves real-time evaluation and dynamic optimization of the randomness of the intermediate key block. The first sub-step provides an evaluation basis by quantifying the stationarity and volatility of the entropy distribution; the second sub-step generates a comprehensive evaluation index by integrating information through weighted averaging; and the third sub-step ensures that the randomness quality meets the standards through dynamic adjustment. From quantitative analysis to comprehensive evaluation and then to dynamic optimization, a complete logical chain is formed, jointly guaranteeing the high quality of the intermediate key block and providing solid technical support for the implementation of dynamic encryption and adaptive security level adjustment methods for flight data.

[0102] Step S5 derives the session key and distributes it to each participating node by analyzing the dispersion of the entropy distribution map, and records it in the entropy history database to provide a reference for key updates, thereby ensuring the confidentiality and integrity of flight data in a dynamic network.

[0103] Step S5 includes the following:

[0104] S5.1, Evaluate the dispersion of the entropy distribution plot:

[0105] The dispersion of the entropy distribution map is evaluated to verify whether the randomness of the intermediate key block meets security requirements. The specific process is as follows: First, an entropy value sequence is extracted from the entropy distribution map, consisting of multiple segments of entropy values. Then, the mean of the entropy value sequence is calculated by summing all entropy values ​​and dividing by the total number of entropy values. Next, the absolute deviation of each entropy value from this mean is calculated by subtracting the mean from each entropy value and taking the absolute value, summing all absolute deviations and dividing by the total number of entropy values ​​to obtain the dispersion index. Finally, this dispersion index is compared with a preset threshold. If the dispersion index is less than or equal to the threshold, the dispersion of the entropy distribution map is deemed to meet the requirements, and the intermediate key block can be used for subsequent session key derivation; otherwise, the process returns to the previous step to adjust the intermediate key block.

[0106] The purpose of evaluating the dispersion of the entropy distribution map is to ensure that the intermediate key block possesses sufficient randomness to meet security standards by quantifying the dispersion of the entropy value sequence. The dispersion index reflects the uniformity of the entropy value distribution; a smaller dispersion index indicates a more uniform entropy distribution and better randomness in the intermediate key block. Through objective quantitative evaluation, the quality of the randomness of the intermediate key block can be effectively verified, ensuring that it maintains high entropy characteristics even in complex network environments, thereby providing reliable security for the encryption system.

[0107] S5.2, Derive the session key:

[0108] The session key is derived based on the intermediate key block. The specific process is as follows: First, the intermediate key block is divided into multiple sub-blocks according to a predefined key length. Then, based on the entropy value corresponding to each sub-block in the entropy distribution diagram, several sub-blocks with the highest entropy values ​​are selected. Next, a bitwise XOR operation is performed on the selected sub-blocks; specifically, the binary bits of these sub-blocks are compared bit by bit. If corresponding bits are the same, the result is zero; if they are different, the result is one, generating a preliminary session key. Finally, a hash function is applied to the preliminary session key, and a fixed-length final session key is generated through a one-way transformation.

[0109] The purpose of deriving the session key is to ensure its high strength and randomness by utilizing the sub-block with the highest entropy value and bitwise XOR operations. Selecting the sub-block with the highest entropy value maximizes the key's entropy content, while bitwise XOR operations enhance the key's complexity through bit-level operations, and the one-way nature of the hash function further improves the key's security. The session key generated by this derivation process has high randomness and complexity, which can significantly improve the encryption system's resistance to attacks and effectively protect the confidentiality and integrity of flight data.

[0110] S5.3, Issue the session key and write it to the entropy history database:

[0111] The session key is distributed to each participating node and written to the entropy history database. The specific process is as follows: First, the final session key is sent to all participating nodes through a secure channel to ensure that each node receives a consistent key for data encryption and decryption; then, the dispersion index of the current entropy distribution map, the entropy value sequence, and the metadata of the session key generation are recorded in the entropy history database. Specifically, this data is stored in chronological order, and the records in the entropy history database are updated to maintain the timeliness and integrity of the data.

[0112] The purpose of distributing session keys is to ensure that all participating nodes use the same key for data encryption and decryption, thereby maintaining the consistency and security of data transmission. Writing to the entropy history database aims to save relevant data on session key generation, providing a reference for subsequent key updates and ensuring the traceability of the key generation process. This operation ensures the stable operation of the encryption system in complex network environments. By recording and updating historical data, the system can analyze and optimize the key generation process, thereby improving overall security and adaptability.

[0113] Step S5 consists of three sub-steps: evaluating the dispersion of the entropy distribution map, deriving the session key, and issuing the session key and writing it into the entropy history database. Together, they constitute the complete technical logic for intermediate key block processing and session key generation and distribution. The first sub-step verifies the randomness quality of the intermediate key block through the evaluation of the dispersion index. The second sub-step generates a high-strength session key based on the qualified intermediate key block. The third sub-step distributes the generated session key to participating nodes and records relevant data to support system operation. These three sub-steps are sequentially linked, from quality verification to key generation to distribution and recording, forming a tight logical chain to ensure the effective implementation of the dynamic encryption of flight data and the adaptive adjustment of security levels.

[0114] The core idea of ​​"adaptive security level adjustment" in this scheme is essentially to indirectly control encryption strength through a dynamic evaluation and intervention mechanism of randomness quality during key generation, thereby adapting to data protection needs in different flight environments. This idea does not involve explicitly adjusting security level parameters, but rather uses randomness quality as an intermediary variable to dynamically match key strength with the flight security situation, as specifically demonstrated below:

[0115] The random seed quality measurement and duplicate removal in steps S1 and S2 form an accurate characterization of the initial entropy quality, indirectly mapping the data sensitivity and node trust status in the current environment.

[0116] The "node weight level" and "generation time slot" introduced in step S3 serve as a hybrid basis, essentially establishing an adjustment bridge between security level and the behavior of participating nodes. That is, the more important a node is or the closer it is to a high-sensitivity time slot, the greater its data contribution to the key, thereby achieving the adjustment of encryption strength.

[0117] The "preset threshold" introduced in step S4 serves as an adjustment trigger point and can be regarded as a dynamic reference line for the security level. Once the entropy distribution map fails to meet the expected dispersion, it is considered that the current key strength is insufficient, and the system will automatically trigger source replenishment and remixing to actively increase the encryption strength.

[0118] The entropy history database in step S5 not only records the state, but also serves as a reference for the next round of judgment, thereby forming a memory and adaptation to the trend of changes in the security level, enabling the system to have a "feedforward response" to future environmental fluctuations.

[0119] In summary, this solution does not explicitly set the "security level" through a single module, but rather "implicitly encodes" it within multiple interactive logics such as data quality, node weights, and discrete response, thus realizing an "embedded, procedural" adaptive adjustment mechanism for the security level.

[0120] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0121] It should be noted that the system of the present invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting a variety of hardware environments and usage requirements.

[0122] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0123] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely to distinguish one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0124] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for dynamic encryption and adaptive adjustment of security level of flight data, characterized in that, Including the following steps: S1: Synchronously collect the random seeds generated by each node, attach a generation time slot label and quality metric to each random seed, and write it into the seed temporary storage table; S2: Check the seed temporary table according to the order of the generated time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence; S3: Based on the weight level of participating nodes and the generation time slot, the pure entropy index sequence is subjected to staggered rotation mixing, the intermediate key block is output and the entropy distribution map is drawn simultaneously; Step S3 includes the following: The weight of each participating node is calculated based on the type, historical performance, and network stability of the participating nodes. An intermediate key block is generated by interleaving and rotating the weights of the participating nodes according to the pure entropy index sequence. The entropy distribution map of the intermediate key block is calculated and plotted simultaneously to verify its randomness. S4: Real-time evaluation of the randomness of the mixed sequence; when the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map. Step S4 includes the following: The randomness of the intermediate key block is evaluated in real time. The rotational mixing equilibrium distance and discrete breadth amplitude are extracted from the entropy distribution map. The distance-amplitude resonance coefficient is obtained by comprehensive analysis using these two indicators and compared with a preset threshold. If the distance-amplitude resonance coefficient is lower than the preset threshold, additional random numbers are requested from high-trust nodes, incorporated into the mixing process, and the entropy distribution map is updated to ensure that the randomness of the intermediate key block meets the encryption requirements. The logic for obtaining the rotational mixing equilibrium distance is as follows: by dividing the entropy value sequence into sub-intervals, the root mean square difference between the local mean and the global mean of each sub-interval is calculated to measure the stationarity of the entropy distribution. The logic for obtaining the discrete breadth amplitude is as follows: calculate the difference between the maximum and minimum values ​​of the entropy value sequence and divide it by the global mean to measure the dispersion and volatility of the entropy value distribution. S5: After the entropy distribution graph dispersion meets the requirements, the session key is derived based on the intermediate key block and distributed to each participating node.

2. The method for dynamic encryption and adaptive security level adjustment of flight data according to claim 1, characterized in that, Step S1 includes the following: Each participating node synchronously generates a random seed within a predetermined time slot. The time synchronization protocol coordinates all participating nodes to ensure consistent generation time. A generation time slot label and a quality metric are attached to each random seed. The random seed, generation time slot label, and quality metric are written as data units into a seed temporary storage table and stored according to the participating node identifier and time slot sequence number.

3. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 2, characterized in that, Step S2 includes the following: The seed temporary table is checked in chronological order based on the generation time slot label. Data units containing random seeds, generation time slot labels, and quality metric values ​​are sorted and grouped according to their respective time slots. For each time slot, duplicate random seeds from the same participating node are detected and removed by retaining the data unit with the highest quality metric value and discarding the rest. Missing random seeds corresponding to nodes that did not submit random seeds in a specific time slot are identified and marked.

4. The method for dynamic encryption and adaptive security level adjustment of flight data according to claim 3, characterized in that, Step S2 also includes the following: A clean entropy index sequence is generated by extracting random seeds from the updated seed staging table and arranging them in order of generation time slot labels.

5. The method for dynamic encryption and adaptive security level adjustment of flight data according to claim 4, characterized in that, Step S5 includes the following: The dispersion of the entropy distribution map is evaluated in real time. The dispersion is quantified by calculating the mean of the entropy value sequence and the absolute deviation of each entropy value from the mean. The randomness of the intermediate key block is verified by comparing it with a preset threshold. The intermediate key block is divided into segments of a predefined length, the sub-block with the highest entropy value is selected and a bitwise XOR operation is performed to generate a preliminary session key, and then a hash function is applied to generate the final session key.

6. The method for dynamic encryption and adaptive security level adjustment of flight data according to claim 5, characterized in that, Step S5 also includes the following: The final session key is distributed to all participating nodes through a secure channel, and the dispersion index, entropy sequence, and session key generation metadata are recorded in the entropy history database.

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