Dynamic encryption and security level adaptive adjustment method for flight data

Abstract

The invention discloses a dynamic encryption and security level adaptive adjustment method for flight data, particularly relates to the field of data security, and is used for solving the security and integrity problems of the flight data in an unstable network environment. According to the method, the mass of random seeds is quantified in real time in the mixing process, incremental seeds are added once the dispersion is reduced, and weak random source transmission is blocked; the historical track continuously provides threshold correction, so that the secret key updating rhythm and the link fluctuation are kept at the same frequency; a new secret key with sufficient safety margin is output by depending on a structured spin mixing and real-time source supplementing mechanism, and a secret key material keeps double characteristics of high discretization and high independence, so that randomness attenuation caused by packet missing, retransmission or node out-of-step is avoided; meanwhile, security level adjustment logic is deeply coupled with a key generation process, so that adaptive balance of encryption strength and operation load is realized, and the flight data is enabled to maintain collaborative excellent performance of confidentiality, integrity and real-time performance in a complex environment.

Description

Technical Field

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

[0002] During the dynamic encryption and adaptive security level adjustment process for flight data, airborne terminals must regularly update keys with ground stations, satellite relays, or neighboring nodes to ensure the confidentiality and integrity of flight data in various network environments. This process requires each participating node to simultaneously generate high-entropy random numbers and perform multiple rounds of mixing operations according to a predefined mixing strategy to construct a new round of encryption keys. Furthermore, the encryption algorithm and key strength can be rapidly switched between different security levels to ensure a balance between performance and security requirements.

[0003] However, due to the difficulty in accurately synchronizing the packet loss retransmission mechanism and key negotiation trigger conditions in unstable link environments, the random numbers generated by some nodes were not evenly mixed or were reused during retransmission. The entropy distribution of the new key material was severely unbalanced, significantly reducing its randomness. The encryption strength failed to meet security requirements and was vulnerable to side-channel attacks such as statistical analysis, creating security risks for the overall data protection strategy.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for dynamic encryption and adaptive adjustment of the security level of flight data. The method quantifies the quality of the random seed in real time during the mixing process, and adds an incremental seed immediately once the discreteness decreases, thereby blocking the transmission of weak random sources. The historical trajectory continuously provides threshold correction to keep the key update rhythm in sync with the link fluctuation. Relying on structured rotation mixing and real-time source replenishment mechanism, a new key with sufficient security margin is output, and the key material maintains the dual characteristics of high discreteness and high independence to avoid randomness attenuation caused by packet loss, retransmission or node desynchronization. At the same time, the security level adjustment logic is deeply coupled with the key generation process to achieve an adaptive balance between encryption strength and computational load, so that flight data can maintain confidentiality, integrity and real-time collaborative superior performance in complex environments, thereby solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for dynamic encryption and adaptive adjustment of security level of flight data, comprising the steps of: S1: Synchronously collect random seeds generated by each node, attach a generated time slot label and quality metric to each random seed, and write them into the seed temporary storage table; S2: Check the seed temporary storage table in the order of generating time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence; S3: Based on the participating node weights and the generation time slot, the pure entropy index sequence is interleaved and rotated, and the intermediate key block is output and the entropy distribution graph is drawn synchronously; S4: Evaluate the randomness of the mixed sequence in real time. When the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map. S5: After the discreteness of the entropy distribution graph meets the requirements, the session key is derived based on the intermediate key block and sent to each participating node.

[0007] In a preferred embodiment, step S1 includes the following contents: Each participating node synchronously generates a random seed within a predetermined time slot, and coordinates all participating nodes through a time synchronization protocol to ensure consistent generation time. A generation time slot tag and a quality metric are attached to each random seed. The random seed, generation time slot tag, and quality metric are written as data units into a seed temporary storage table, which is organized and stored according to the participating node identifier and time slot sequence number.

[0008] In a preferred embodiment, step S2 includes the following: The temporary storage table of seeds is checked in chronological order according to the generation time slot labels, and the data units containing random seeds, generation time slot labels and quality metrics 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 at a specific time slot are identified and marked.

[0009] In a preferred embodiment, step S2 further includes the following: Generate a clean entropy index sequence by extracting random seeds from the updated seed temporary storage table and arranging them in the order of generating time slot labels.

[0010] In a preferred embodiment, step S3 includes the following contents: The weight of each participating node is calculated based on the type, historical performance and network stability of the participating nodes. The intermediate key block is generated through the interleaved rotation mixing technology based on the pure entropy index sequence and the participating node weight. The entropy distribution diagram of the intermediate key block is simultaneously calculated and plotted to verify its randomness.

[0011] In a preferred embodiment, step S4 includes the following contents: The randomness of the intermediate key block is evaluated in real time. The rotational mixing balance distance and discrete breadth amplitude are extracted from the entropy distribution map. The distance-amplitude resonance coefficient is obtained by comprehensive analysis of these two indicators and compared with the 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.

[0012] In a preferred embodiment, step S4 further includes the following: The logic for obtaining the rotating hybrid equilibrium distance is as follows: the entropy value sequence is divided into subintervals, and the root mean square difference between the local mean and the global mean of each subinterval is calculated to measure the stationarity of the entropy distribution.

[0013] In a preferred embodiment, step S4 further includes the following: The logic for obtaining the discrete breadth amplitude is to calculate the difference between the maximum and minimum values ​​of the entropy value sequence and divide it by the global mean to measure the discreteness and volatility of the entropy value distribution.

[0014] In a preferred embodiment, step S5 includes the following contents: The discreteness of the entropy distribution graph is evaluated in real time. The discreteness is quantified by calculating the mean of the entropy value sequence and the absolute deviation of each entropy value from the mean, and the randomness of the intermediate key block is verified by comparing it with the preset threshold. The preliminary session key is generated based on the intermediate key block being split according to a predefined length, the sub-block with the highest entropy value is selected and a bitwise XOR operation is performed, and then the final session key is generated by applying a hash function.

[0015] In a preferred embodiment, step S5 further includes the following: The final session key is sent to all participating nodes through a secure channel, and the dispersion index, entropy value sequence and session key generation metadata are recorded in the entropy history library.

[0016] The technical effects and advantages of the method for dynamic encryption and adaptive adjustment of security level of flight data of the present invention are as follows: The present invention constructs a progressive link through time-tagged random seeds, sliding sequence verification and purification, rotational interleaving and mixing, distribution balancing inspection and two-way historical backtracking deduction. The output of each link is both verified and reshaped in the next link, forming a random diffusion system with space-time interweaving. The quality of the random seed is instantly quantified during the mixing process. Once the discreteness decreases, the incremental seed is immediately added to block the transmission of weak random sources; the historical trajectory continuously provides threshold correction to keep the key update rhythm in sync with the link fluctuation. The entire process does not require centralized weighting, relying on structured rotation mixing and real-time source replenishment mechanisms to continuously output new keys with sufficient security margins within limited computing power. The key material maintains the dual characteristics of high discreteness and high independence to avoid randomness attenuation caused by packet loss, retransmission or node desynchronization; at the same time, the security level adjustment logic is deeply coupled with the key generation process to achieve an adaptive balance between encryption strength and computing load, so that flight data can maintain confidentiality, integrity and real-time collaborative superior performance in complex environments such as high-speed maneuvers and cross-domain switching. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The figure is a flow chart of a method for dynamic encryption and adaptive adjustment of security level of flight data according to the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] Example 1: Figure 1 The present invention provides a method for dynamic encryption and adaptive adjustment of security level of flight data, including: S1: Synchronously collect random seeds generated by each node, attach a generated time slot label and quality metric to each random seed, and write them into the seed temporary storage table; S2: Check the seed temporary storage table in the order of generating time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence; S3: Based on the participating node weights and the generation time slot, the pure entropy index sequence is interleaved and rotated, and the intermediate key block is output and the entropy distribution graph is drawn synchronously; S4: Evaluate the randomness of the mixed sequence in real time. When the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map. S5: After the discreteness of the entropy distribution graph meets the requirements, the session key is derived based on the intermediate key block and sent to each participating node.

[0020] In modern aviation communications, the security of flight data is paramount. Flight data includes sensitive information such as flight paths, navigation parameters, and communication logs. During transmission, this data must interact with multiple nodes, including onboard terminals, ground stations, satellite relays, and neighboring nodes. Because aircraft operate in complex environments such as high-speed maneuvers and cross-domain handoffs, network links often experience instability, such as packet loss and retransmissions. This can lead to insufficient randomness in encryption key generation, thereby reducing data protection. To address this challenge, a method for dynamic encryption of flight data and adaptive security level adjustment is proposed. This method ensures data confidentiality, integrity, and real-time performance by regularly updating encryption keys and adaptively adjusting the security level based on the network environment. Key updates rely on high-entropy random seeds generated by each node, generating new keys through multiple rounds of mixing operations. However, if the random seeds are not collected correctly or reused due to network issues, the randomness of the new keys will decrease, making them vulnerable to side-channel attacks. Therefore, step S1, the starting point of the entire process, aims to synchronously collect random seeds from each node and attach key tags to them, providing high-quality initial material for subsequent steps and laying the foundation for key generation.

[0021] Step S1 includes the following contents: S1.1, synchronously collect random seeds: Each participating node, including airborne terminals, ground stations, satellite relays, and neighboring nodes, simultaneously generates a random seed within a predetermined time period. These predetermined time periods are defined as time slots, which are arranged in sequence. All participating nodes use a unified time synchronization protocol to ensure that the random seed generation process is triggered simultaneously at the start of each time slot. Each participating node independently generates a highly random value at the beginning of a time slot, called a random seed. The random seed generation process relies on the random number generation mechanism within each participating node to ensure that the generated random seed is sufficiently unpredictable. Random seeds are collected synchronously, and the behavior of all participating nodes is coordinated through a time synchronization protocol to ensure that the random seed generation time is consistent, avoiding time mismatches caused by network transmission delays or clock deviations of participating nodes.

[0022] The purpose of synchronous random seed collection 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 order confusion or security vulnerabilities caused by time misalignment. This can effectively prevent random seed generation time differences caused by unstable network environments and improve the time consistency of input data during the key generation process.

[0023] S1.2, additional generation of slot labels: A generation slot tag is attached to each random seed. The generation slot tag identifies the time slot corresponding to the random seed generation time, specifically the sequence number of the time slot in which the random seed was generated. This generation slot tag is attached immediately after the random seed is generated. Each participating node binds the sequence number of the time slot to the corresponding random seed, forming a complete data unit containing time information. This generation slot tag ensures that each random seed carries a clear identification of its generation time, facilitating chronological verification and organization of random seeds in subsequent processing.

[0024] The purpose of attaching a generation time slot tag to the random seed is to provide time traceability, enabling the system to identify the random seed generation order in subsequent steps and detect duplication or misordering caused by network retransmission or delays, thereby maintaining temporal consistency in data processing. Effectively managing random seeds through time tags reduces processing errors caused by time misalignment and provides a reliable time reference for subsequent filtering and mixing operations.

[0025] S1.3, Calculate and attach quality metrics: A quality metric is calculated and appended to each random seed to assess its level of randomness. The quality metric calculation process includes the following steps: First, the uniformity of the distribution of 0s and 1s in the random seed's bit sequence is analyzed to determine the actual entropy 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. The effective bit length refers to the number of valid bits remaining after removing repeated or invalid bits caused by defects in the random number generator. Finally, the ratio of the actual entropy to the theoretical maximum entropy is calculated. The theoretical maximum entropy is the maximum possible entropy 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 a quality metric. The quality metric is numerically appended to the corresponding random seed data unit.

[0026] The purpose of calculating and attaching quality metrics is to quantify the randomness and validity of random seeds, ensuring that only random seeds that meet high quality standards are used for key generation, thereby improving the security of the keys. Quality metrics provide an objective basis for screening random seeds, eliminating those with insufficient randomness or defects, thereby enhancing the attack resistance of newly generated keys and ensuring the security of encryption systems.

[0027] S1.4, write to the temporary seed storage table: The collected random seeds and related information, including the random seeds themselves, generated time slot labels, and quality metrics, are written into a structured storage unit called a seed temporary storage table. The seed temporary storage table organizes data according to the participating node identifiers and time slot numbers to form an ordered storage structure. The writing process specifically includes: after receiving a data unit containing a random seed, generated time slot label, and quality metric, the corresponding storage location in the seed temporary storage table is determined based on the generated time slot label and participating node identifier; if the location is empty, the data unit is written directly; if other data units are already stored in the location, the quality metrics of the new and old data units are compared, the data units with higher quality metrics are retained, and the data units with lower quality metrics are discarded to avoid interference from duplicate data.

[0028] Step S1 constructs a high-quality, time-consistent random seed set through synchronous collection, time tagging, quality assessment, and structured storage, providing reliable input data for key generation for dynamic encryption of flight data. Synchronous collection ensures the temporal coordination of random seed generation, while the generation of time slot tags provides time traceability and sequence management capabilities. The calculation and addition of quality metrics ensure the randomness and validity of the random seeds, and writing to the seed temporary storage table facilitates orderly storage and efficient data processing. This ensures strict control of random seed quality and consistency at the initial stages of the key generation process. Multi-layered technical measures address randomness decay in unstable network environments, thereby ensuring the security and stability of the entire encryption system.

[0029] Step S1 has completed the synchronous collection of random seeds generated by each participating node, and attached a generated time slot label and quality metric to each random seed, and written this information into the seed temporary storage table. The data units in the seed temporary storage table provide the basic materials for subsequent key generation, including random seeds, generated time slot labels and quality metrics. However, due to the instability of the flight data transmission link, such as packet loss or retransmission, random seeds may be repeated or missing in the seed temporary storage table, which directly affects 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 basis for the interleaved rotation mixing operation in step S3.

[0030] The specific processing technology logic of step S2 includes 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.

[0031] Step S2 includes the following contents: S2.1, check the temporary seed storage table in chronological order: The data units in the seed temporary table are sorted and verified by the sequence number of the generated time slot tag. The seed temporary table contains multiple data units, each consisting of a random seed, a generated time slot tag, and a quality metric. The processing process first reads all data units in the seed temporary table and sorts them in ascending order by the sequence number of the generated time slot tag, forming a temporally ordered set of data units. After sorting, the data units are divided into multiple groups based on the generated time slot tag. Each group corresponds to a time slot and contains the random seeds and quality metrics submitted by all participating nodes in that time slot. Next, a duplicate check is performed on the data units in each time slot to check whether there are multiple random seeds submitted by the same participating node. If the same participating node submits multiple data units 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 eliminated. Furthermore, a missing check is performed on each time slot to verify the submission status of all participating nodes. If a participating node fails to submit a random seed, the missing status of the participating node in that time slot is recorded.

[0032] The purpose of chronologically verifying the seed staging table is to ensure that data processing follows the chronological order of random seed generation, maintain temporal consistency, and avoid random seed misordering or duplication caused by network transmission delays or retransmissions. By sorting and verifying the seed staging table in chronological order, duplicate and missing random seeds can be promptly identified and addressed, improving the traceability and accuracy of data processing.

[0033] S2.2, remove duplicate or missing random seeds: Based on the seed temporary storage table that has been checked in chronological order, the data units are purified to remove duplicate or missing random seeds, ensuring that each participating node retains only one high-quality random seed in each time slot. The specific processing process is as follows: 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 did not submit a random seed, their random seed is marked as missing, and the record is retained in the seed temporary storage table. After completing duplicate removal and missing marking, an updated seed temporary storage table is generated, in which the data unit corresponding to each participating node in each time slot is either a unique high-quality data unit or marked as missing. The updated seed temporary storage table retains the complete structure of all time slots while ensuring the quality and uniqueness of the data units.

[0034] 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 data. By purifying data units, errors caused by redundant 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.

[0035] S2.3, generate a pure entropy index sequence: Based on the updated temporary seed table, a pure entropy index sequence is generated. The specific generation process is as follows: The random seeds of all participating nodes in each time slot are extracted from the updated temporary seed table. For participating nodes marked as missing, their random seed values ​​are set to null. The extracted random seeds are then sorted from smallest to largest according to the sequence number of the generated time slot labels to ensure 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 random seeds are arranged strictly in 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.

[0036] The purpose of generating a pure entropy index sequence is to provide high-quality, time-consistent input data for subsequent interleaving, rotation, and mixing 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, improving the randomness and anti-attack capabilities of the key material.

[0037] Step S2 efficiently cleans and organizes random seed data through three sub-steps: chronologically verifying the temporary seed table, removing duplicate or missing random seeds, and generating a clean entropy index sequence. First, temporal consistency is established through time sorting and verification. Then, data quality is ensured by removing duplicates and marking missing data. Finally, sequence generation provides high-quality input. This entire process effectively addresses the issue of duplicate or missing random seeds caused by link instability, improves the reliability and security of key generation, and provides a solid technical foundation for the implementation of dynamic encryption of flight data and adaptive security level adjustment methods.

[0038] Based on the seed temporary storage table, step S2 checks the 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 cause uneven quality or imbalanced distribution of random seeds for some nodes. If the pure entropy index sequence is used directly to generate keys, it may not meet the requirements of high randomness and security and be vulnerable to statistical analysis attacks. To this end, step S3 needs to use specific hybrid technology to further improve the randomness and security of the pure entropy index sequence, generate an intermediate key block, and ensure its entropy distribution is balanced, to support the randomness evaluation of the subsequent step S4 and the derivation of the session key in step S5.

[0039] The specific processing technology logic of step S3 includes three sub-steps: determining the weight level of participating nodes, implementing staggered rotation mixing, and synchronously drawing an entropy distribution map.

[0040] Step S3 includes the following contents: S3.1, determine the participating node rights level: First, each participating node is assigned a weight to quantify its influence and trustworthiness 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 an airborne terminal is set to 1.0, the coefficient for a ground station is set to 0.8, and the coefficient for a satellite relay is set to 0.9.

[0041] The historical performance coefficient is based on the average quality of random seeds submitted by the 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 a more stable network connection.

[0042] The weight calculation process is as follows: first, 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 are calculated. These three products are then added together, and the result is divided by the sum of the node type coefficient, the historical performance coefficient, and the network stability coefficient to obtain the final weight value. This calculation method comprehensively considers the node's inherent attributes, historical performance, and real-time network status, avoiding the dominance of a single factor and ensuring that the weight fully reflects the node's characteristics.

[0043] The purpose of assigning weights to participating nodes is to give different nodes varying influence during the key generation process, ensuring that nodes with high security, excellent performance, and stable networks contribute more to key generation, thereby improving the randomness and security of the keys. This weighting mechanism leverages the reliability, historical performance, and network stability of nodes, enhancing the adaptability and robustness of the key generation process and ensuring high-quality key material generated in a volatile network environment.

[0044] S3.2, implement staggered rotation mixing: Based on the pure entropy index sequence and the weight level of the participating nodes, an interleaved rotation is performed to generate an intermediate key block. The specific process includes the following stages: First, the pure entropy index sequence is divided into multiple subsequences according to the time slot. Each subsequence contains the random seeds of all participating nodes in the time slot. Then, within each time slot, the random seeds are sorted from high to low according to the weight of the participating nodes. Next, a rotation operation is performed on the sorted random seed list. If the number of random seeds is even, a pair of seeds is taken from the beginning and end of the list and XORed to generate a mixed seed. If the number of random seeds is odd, the seed in the middle of the list is retained unchanged, and the remaining pairs of seeds are XORed to generate a mixed seed. Afterwards, 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 XORed at the corresponding positions is performed based on the time slot with the smaller number, and the excess mixed seeds are retained unchanged. Finally, the interleaved mixed seeds of all time slots are concatenated according to the time slot order and the mixed seed sequence number to generate the intermediate key block.

[0045] The purpose of implementing interleaved rotation mixing is to increase the complexity of the mixing process through weighted sorting and rotation operations. Interleaving operations enhance the data correlation between time slots, ensuring that the intermediate key blocks possess high randomness and strong entropy properties. This mixing technique significantly improves the randomness and security of the random seed, reduces the risk of randomness degradation caused by unstable communication links or node data desynchronization, and provides high-quality intermediate material for subsequent session key generation.

[0046] S3.3, synchronously draw the entropy distribution map: 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 segmented into fixed-length segments. Then, for each segment, the probability of occurrence of the bit values ​​within it is calculated, and the entropy value of each segment is calculated based on this probability. The entropy value is calculated based on the Shannon entropy principle, which is a weighted summation of the bit value occurrence probabilities. Next, a line chart is drawn with the segment number as the horizontal axis and the entropy value of each segment as the vertical axis, showing the distribution trend of the entropy value as the segment changes. At the same time, a pre-set entropy threshold is set. If the entropy value of a segment falls below this threshold, the segment is marked as abnormal and its sequence number is recorded for subsequent processing.

[0047] The purpose of synchronous entropy mapping is to monitor the randomness of intermediate key blocks in real time, ensuring they meet high entropy requirements and providing a visual basis for subsequent randomness verification and optimization. By mapping the entropy distribution and detecting anomalies, we can promptly identify sections with insufficient randomness and implement targeted actions, improving the transparency and controllability of the key generation process and ensuring the overall security of the encryption system.

[0048] Step S3 achieves efficient reorganization and enhanced randomness of the pure entropy index sequence through three sub-steps: determining the weights of participating nodes, implementing interleaved rotation mixing, and simultaneously plotting an entropy distribution map. The first sub-step optimizes the contribution ratio of participating nodes through weight allocation, the second sub-step enhances data complexity and randomness through interleaved rotation mixing, and the third sub-step verifies and ensures the quality of the intermediate key block through the entropy distribution map. These three sub-steps are closely linked and together ensure the high randomness and strong security of the intermediate key block, providing solid technical support for the implementation of dynamic encryption of flight data and adaptive security level adjustment methods.

[0049] Steps S1 to S3 have completed the collection, verification, mixing and entropy distribution map of random seeds, generated an intermediate key block and preliminarily evaluated its 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, which may lead to packet loss or retransmission, the random seeds of some nodes fail to participate in the mixing evenly, or the entropy distribution map shows that the convergence deviation exceeds the standard, resulting in insufficient randomness of the intermediate key block. If such an intermediate key block is used directly to derive the session key, the encryption strength will be significantly reduced and it will be vulnerable to side channel attacks. To this end, step S4 needs to introduce a real-time evaluation and dynamic adjustment mechanism to ensure that the quality of the intermediate key block meets security requirements and provide reliable key material for step S5.

[0050] Step S4 includes the following contents: S4.1, extract the rotation mixing balance distance and discrete width: Two parameters, the mixing distance and the discrete width, are extracted to quantify the randomness of the intermediate key block. The mixing distance measures the stability of the entropy value sequence in the entropy distribution graph as the segment number changes. Its calculation process is as follows: first, the entropy value sequence is divided into multiple subintervals, and then the local mean of each subinterval and the global mean of the entire entropy value sequence are calculated. Then, the difference between the local mean and the global mean of each subinterval is calculated, and the square root of all the differences is summed. The result is the mixing distance. The smaller the value, the more stable the entropy distribution.

[0051] The discrete width measures the degree of discreteness of the entropy value sequence. The calculation process is: extract the maximum and minimum values ​​of the entropy value sequence, calculate the difference between the two, and then divide this difference by the global mean to obtain the discrete width. The larger the value, the stronger the entropy value volatility.

[0052] The purpose of extracting the rotation mixing balance distance and discrete width is to comprehensively assess the randomness quality of the intermediate key block by quantifying the stationarity and volatility of the entropy distribution. Relying on a single metric cannot fully reflect the characteristics of the entropy distribution. These two parameters provide complementary information from the two dimensions of stationarity and discreteness, respectively. This quantification method can intuitively reflect the overall characteristics and local variations of the entropy distribution, providing an accurate and objective assessment basis, facilitating subsequent comprehensive analysis and adjustment.

[0053] S4.2, calculate the amplitude resonance coefficient: The distance-amplitude resonance coefficient is calculated based on the mixing and balancing distance and the discrete width. The calculation process is as follows: First, preset weights are set for the mixing and balancing distance and the discrete width, respectively. The weights reflect the different importance of stability and volatility to the randomness assessment. Then, the mixing and balancing distance are multiplied by their corresponding weights, and the discrete width is multiplied by its corresponding weights, 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 evaluation indicator of randomness.

[0054] S4.3, determine and request incremental random numbers: A preset threshold is set, and based on the comparison of the distance-amplitude resonance coefficient with the preset threshold, the randomness of the intermediate key block is determined to be up to standard. The processing process is as follows: the calculated distance-amplitude resonance coefficient is compared with the preset threshold. If the distance-amplitude resonance coefficient is lower than the preset threshold, a request is sent to a 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. The aforementioned steps of extracting the rotation-mixing balance distance and discrete width, and calculating the distance-amplitude resonance coefficient are then repeated until the distance-amplitude resonance coefficient reaches or exceeds the preset threshold.

[0055] High-trust nodes refer to pre-set, trusted nodes in the network. They are specially designated for their high reliability and trustworthiness and are usually used to ensure the security and stability of the system.

[0056] The purpose of determining and requesting incremental random numbers is to ensure that the randomness of the intermediate key block consistently meets security requirements through a dynamic adjustment mechanism. When the amplitude-to-range resonance coefficient falls below a preset threshold, it indicates insufficient randomness and requires the introduction of an external, high-quality random source for improvement. This adaptive source replenishment mechanism promptly responds to insufficient randomness and improves the quality of the intermediate key block by introducing incremental random numbers, thereby enhancing the encryption system's resilience and security.

[0057] Step S4 implements real-time evaluation and dynamic optimization of the randomness of the intermediate key block through three sub-steps: extracting the rotation-mixing balance distance and discrete width, calculating the distance-amplitude resonance coefficient, and determining and requesting an incremental random number. The first sub-step provides an evaluation basis by quantifying the stationarity and volatility of the entropy distribution. The second sub-step integrates this information through weighted averaging to generate a comprehensive evaluation index. The third sub-step ensures that randomness quality meets standards through dynamic adjustment. From quantitative analysis to comprehensive evaluation to dynamic optimization, a complete logical chain is formed, which collectively ensures the high quality of the intermediate key block and provides solid technical support for the implementation of dynamic encryption of flight data and adaptive adjustment of security levels.

[0058] Step S5 derives the session key by analyzing the discreteness of the entropy distribution graph and distributes it to each participating node. It also records it in the entropy history library to provide a reference for key updates, thereby ensuring the confidentiality and integrity of flight data in a dynamic network.

[0059] Step S5 includes the following contents: S5.1, Evaluate the dispersion of the entropy distribution graph: The dispersion of the entropy distribution graph is evaluated to verify whether the randomness of the intermediate key block meets security requirements. The specific processing process is as follows: first, an entropy value sequence is extracted from the entropy distribution graph. This sequence consists of multiple segmented entropy values. Then, the mean of the entropy value sequence is calculated, that is, the average is obtained by adding all the entropy values ​​and dividing it by the total number of entropy values. Next, the absolute deviation of each entropy value from the mean is calculated. Specifically, the absolute value of each entropy value is subtracted from the mean, and the absolute value of all the absolute deviations is added and divided by the total number of entropy values ​​to obtain a 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 entropy distribution graph is determined to meet the dispersion requirements and the intermediate key block can be used for subsequent derivation of the session key. Otherwise, the process returns to the previous step to adjust the intermediate key block.

[0060] The purpose of evaluating the dispersion of the entropy distribution graph 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 metric reflects the uniformity of the entropy distribution. A lower dispersion metric indicates a more uniform entropy distribution and better randomness of the intermediate key block. This objective quantitative assessment effectively verifies the randomness quality of the intermediate key block, ensuring that it maintains high entropy properties even in complex network environments, thereby providing reliable protection for the security of the encryption system.

[0061] S5.2, derive the session key: The session key is derived based on the intermediate key block. The specific processing process is as follows: first, the intermediate key block is split into multiple sub-blocks according to the predefined key length; then, based on the entropy value corresponding to each sub-block in the entropy distribution map, several sub-blocks with the highest entropy values ​​are selected; then, a bit-by-bit XOR operation is performed on the selected sub-blocks, specifically comparing the binary bits of these sub-blocks bit by bit. If the corresponding bits are the same, the result is zero; if they are different, the result is one, thus 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.

[0062] The purpose of deriving the session key is to utilize the sub-blocks with the highest entropy values ​​and a bitwise XOR operation to ensure high strength and randomness. Selecting the sub-blocks with the highest entropy values ​​maximizes the key's entropy content. The bitwise XOR operation enhances the key's complexity through bit-level manipulation, while the one-way nature of the hash function further enhances the key's security. This derivation process generates a highly random and complex session key, significantly improving the encryption system's resilience to attacks and effectively protecting the confidentiality and integrity of flight data.

[0063] S5.3, issue the session key and write it into the entropy history library: The session key is distributed to each participating node and written into the entropy history library. The specific processing 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 the same key for data encryption and decryption; then, the dispersion index of the current entropy distribution graph, the entropy value sequence, and the generated metadata of the session key are recorded in the entropy history library. Specifically, this data is stored in chronological order and the records in the entropy history library are updated to maintain the timeliness and integrity of the data.

[0064] The purpose of issuing 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 repository is to preserve data related to 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 supports analysis and optimization of the key generation process, thereby improving overall security and adaptability.

[0065] The three substeps of step S5—evaluating the discreteness of the entropy distribution graph, deriving the session key, and issuing the session key and writing it to the entropy history repository—together constitute the complete technical logic for intermediate key block processing and session key generation and distribution. The first substep verifies the randomness quality of the intermediate key block by evaluating the discreteness metric. The second substep generates a high-strength session key based on the qualified intermediate key block. The third substep distributes the generated session key to participating nodes and records the relevant data to support system operation. These three substeps are linked sequentially, from quality verification to key generation to distribution and recording, forming a strict logical chain, ensuring the effective implementation of dynamic flight data encryption and adaptive security level adjustment methods.

[0066] The core concept of "adaptive security level adjustment" in this solution is to indirectly control encryption strength through dynamic evaluation and intervention of randomness quality during key generation, thereby adapting to data protection requirements in different flight environments. This concept does not rely on explicit adjustment of security level parameters, but rather uses randomness quality as an intermediary variable to dynamically match key strength with flight safety status. The specific implementation is as follows: The random seed quality measurement and duplicate elimination 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.

[0067] The "node weight level" and "generation time slot" introduced in step S3 serve as a hybrid basis, essentially establishing a regulatory bridge between the security level and the behavior of participating nodes. That is, the more important the node or the closer it is to the high-sensitivity time slot, the greater the contribution of its data to the key, thereby achieving upward and downward adjustment of the encryption strength.

[0068] 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 graph fails to meet the expected discreteness, it is considered that the current key strength is insufficient. The system will automatically trigger source replenishment and remixing, and actively increase the encryption strength.

[0069] The entropy history library in step S5 not only records the status, but also serves as a reference for the next round of judgment, thereby forming a memory and adaptation to the changing trend of the security level, so that the system has a "feedforward response" to future environmental fluctuations.

[0070] In summary, this solution does not explicitly set the "security level" through a single module, but "implicitly encodes" it in multiple interactive logics such as data quality, node weight level, and discrete response, realizing an "embedded, procedural" security level adaptive adjustment mechanism.

[0071] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0072] It should be noted that the system of the present invention can be deployed on the device itself to realize embedded applications, and can also be run on a PC or other terminal with a user interface, thereby meeting a variety of hardware environments and usage requirements.

[0073] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

[0074] It should be noted that, in this document, if there are relational terms such as first and second, etc., they are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article or device. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0075] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for dynamic encryption and adaptive adjustment of security level of flight data, characterized in that: Including steps: S1: Synchronously collect random seeds generated by each node, attach a generated time slot label and quality metric to each random seed, and write them into the seed temporary storage table; S2: Check the seed temporary storage table in the order of generating time slot labels, remove duplicate or missing random seeds, and generate a pure entropy index sequence; S3: Based on the participating node weights and the generation time slot, the pure entropy index sequence is interleaved and rotated, and the intermediate key block is output and the entropy distribution graph is drawn simultaneously; S4: Evaluate the randomness of the mixed sequence in real time. When the randomness is insufficient, request high-trust nodes to submit incremental random numbers and remix to update the entropy distribution map. S5: After the discreteness of the entropy distribution graph meets the requirements, the session key is derived based on the intermediate key block and sent to each participating node.

2. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 1, characterized in that: Step S1 includes the following contents: Each participating node synchronously generates a random seed within a predetermined time slot, and coordinates all participating nodes through a time synchronization protocol to ensure consistent generation time. A generation time slot tag and a quality metric are attached to each random seed. The random seed, generation time slot tag, and quality metric are written as data units into a seed temporary storage table, which is organized 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 contents: The temporary storage table of seeds is checked in chronological order according to the generation time slot labels, and the data units containing random seeds, generation time slot labels and quality metrics 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 at a specific time slot are identified and marked.

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

5. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 4, characterized in that: Step S3 includes the following contents: The weight of each participating node is calculated based on the type, historical performance and network stability of the participating nodes. The intermediate key block is generated through the interleaved rotation mixing technology based on the pure entropy index sequence and the participating node weight. The entropy distribution diagram of the intermediate key block is simultaneously calculated and plotted to verify its randomness.

6. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 5, characterized in that: Step S4 includes the following contents: The randomness of the intermediate key block is evaluated in real time. The rotational hybrid balance distance and discrete breadth amplitude are extracted from the entropy distribution map. The distance-amplitude resonance coefficient is obtained by comprehensive analysis of these two indicators and compared with the 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.

7. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 6, characterized in that: Step S4 also includes the following: The logic for obtaining the rotating hybrid equilibrium distance is as follows: the entropy value sequence is divided into subintervals, and the root mean square difference between the local mean and the global mean of each subinterval is calculated to measure the stationarity of the entropy distribution.

8. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 7, characterized in that: Step S4 also includes the following: The logic for obtaining the discrete breadth amplitude is to calculate the difference between the maximum and minimum values ​​of the entropy value sequence and divide it by the global mean to measure the discreteness and volatility of the entropy value distribution.

9. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 8, characterized in that: Step S5 includes the following contents: The discreteness of the entropy distribution graph is evaluated in real time. The discreteness is quantified by calculating the mean of the entropy value sequence and the absolute deviation of each entropy value from the mean, and the randomness of the intermediate key block is verified by comparing it with the preset threshold. The preliminary session key is generated based on the intermediate key block being split according to a predefined length, the sub-block with the highest entropy value is selected and a bitwise XOR operation is performed, and then the final session key is generated by applying a hash function.

10. The method for dynamic encryption and adaptive adjustment of security level of flight data according to claim 9, characterized in that: Step S5 also includes the following: The final session key is sent to all participating nodes through a secure channel, and the dispersion index, entropy value sequence and session key generation metadata are recorded in the entropy history library.

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