Low-altitude unmanned aerial vehicle data security transmission system and method based on edge computing

Abstract

This invention discloses a secure data transmission system and method for low-altitude unmanned aerial vehicles (UAVs) based on edge computing, relating to the field of secure data transmission technology for low-altitude UAVs. This invention assigns a unique and tamper-proof identity to all participating UAVs, edge computing nodes, and cloud functional modules. After collecting operational data and performing deduplication and anomaly removal preprocessing, the UAV initiates an access request to the nearest edge node. The entire link completes bidirectional identity verification and pre-verification of abnormal traffic. The edge node fragments and encrypts the data, then schedules multi-link parallel transmission based on the overall link status. The cloud receives the fragments, decrypts and aggregates them to complete business analysis. The entire link transmission log is retained to support secure traceability. This invention can improve the stability of data transmission in complex low-altitude communication environments, reduce the security risks of data leakage, tampering, and unauthorized access, reduce cloud computing power and bandwidth consumption, and adapt to the needs of different types of low-altitude UAV operational scenarios.

Description

Technical Field

[0001] This invention relates to the field of low-altitude unmanned aerial vehicle (UAV) data security transmission technology, and in particular to a low-altitude UAV data security transmission system and method based on edge computing. Background Technology

[0002] The application of low-altitude drones in scenarios such as power line inspection, agricultural and forestry plant protection, land surveying, and emergency rescue continues to expand. The volume of flight status data, sensor-collected data, and high-definition image data generated during these operations is constantly increasing, placing higher demands on the real-time performance, reliability, and security of data transmission. Currently, the low-altitude communication environment is significantly affected by factors such as building obstruction, signal interference, and drone mobility, making it difficult to guarantee the stability of single-link transmission. At the same time, security risks during drone data transmission, such as identity forgery, data eavesdropping, content tampering, and abnormal injection, are continuously increasing. Existing transmission architectures and security protection mechanisms are no longer adequate to meet the actual needs of complex low-altitude operational scenarios.

[0003] The existing mainstream low-altitude drone data transmission solutions are mainly divided into two categories. One is the end-to-cloud direct connection transmission solution, in which the data collected by the drone is directly uploaded to the cloud management platform through a single communication link. During the transmission process, a fixed key is used to encrypt the entire data packet. This type of solution has a low deployment cost and is widely used in small-scale drone operation scenarios. However, single-link transmission has a high packet loss rate and large latency fluctuation in low-altitude obstruction environments. In the whole-packet encryption mode, once the key is leaked, all transmitted data will be lost. At the same time, a large number of drones directly connecting to the cloud will overload the cloud computing and bandwidth resources. Since no security verification node is set up on the edge side, abnormal access traffic can directly reach the cloud, increasing the security protection pressure on the cloud. Another type is edge-assisted transmission solutions, which relay drone data by deploying edge nodes at low altitudes. This type of solution can reduce transmission latency to some extent, but most solutions only use edge nodes as data forwarding nodes and do not deploy security verification and encryption capabilities on the edge side. The routing scheduling process only refers to transmission performance parameters such as bandwidth and latency, and does not include the historical security events and current security status of the link in the scheduling reference dimension. This makes it easy to select transmission links with security vulnerabilities, leading to data leakage. At the same time, identity authentication often adopts a one-way verification mode, and illegal nodes can access the transmission link by forging identities to steal or tamper with the transmitted data.

[0004] In current low-altitude drone operation scenarios, different services have different requirements for transmission rate and security level. Some classified operation scenarios have extremely high requirements for data security, while some emergency operation scenarios have extremely high requirements for real-time transmission. Existing transmission solutions cannot dynamically adjust transmission strategies and security protection levels according to business needs, making it difficult to simultaneously meet transmission performance and security protection requirements. The end-to-end transmission log retention mechanism is imperfect, making it impossible to complete full-process tracing after a security incident occurs. Summary of the Invention

[0005] This invention proposes a secure data transmission system and method for low-altitude unmanned aerial vehicles (UAVs) based on edge computing, in order to solve the problems mentioned in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a low-altitude unmanned aerial vehicle (UAV) data security transmission system based on edge computing, comprising a unified identity authentication module, a raw data acquisition module, a pre-security verification module, a fragmented encryption processing module, a routing scheduling module, and an aggregation decryption module; wherein, The unified identity authentication module is deployed across the entire data transmission chain, and uses blockchain to assign unique and tamper-proof identity identifiers to drones, edge computing nodes and cloud management platforms. The raw data acquisition module is deployed on the low-altitude UAV terminal to collect UAV flight status data, airborne sensor operation data and positioning data in real time. The acquisition frequency is adjusted according to the operation type, redundancy filtering and format normalization are performed on the collected data, and the processed data is sent to the edge computing node cluster. The front-end security verification module is deployed on the edge computing node cluster. Based on the identity identifier and permission rules generated by the unified identity authentication module, it performs identity legality verification, access permission verification and abnormal traffic identification on data requests from drones, and intercepts unauthorized requests. The data fragmentation encryption module is deployed in the edge computing node cluster. It performs dynamic fragmentation processing on the data to be transmitted that has passed the security verification and uses a symmetric encryption algorithm to configure an independent verification identifier and encryption key for each data fragment. The routing and scheduling module is deployed on the edge computing node cluster. It obtains the encrypted fragments output by the fragment encryption processing module, acquires the network link status in real time based on the SDN architecture, and performs multi-link parallel transmission of encrypted fragments by comprehensively considering edge node load, transmission link bandwidth and link latency data. The aggregation and decryption module is deployed on a cloud management platform. It receives all data fragments transmitted in parallel, performs decryption and aggregation operations after verifying the integrity of the fragments, and restores the complete original transmitted data.

[0007] Furthermore, it also includes a dynamic key update module, which dynamically updates the independent keys corresponding to each shard according to the data sensitivity level, the current transmission link security status, and the preset update cycle. The key update process uses an encrypted and secure synchronous distribution method to synchronize the shard key information between the edge node and the cloud. The keys are generated by a hardware true random number generator.

[0008] Furthermore, it also includes a link security assessment module, which performs real-time assessment of the overall status of all available transmission links. The calculation logic of the link comprehensive security score during route scheduling satisfies the following formula: ;in, A comprehensive security score representing the target transmission link; Represents the bandwidth weighting coefficient; Normalized value representing the available bandwidth of the target transmission link; Represents the packet loss rate weighting coefficient; Represents the packet loss rate of the target transmission link; Represents the delay weighting coefficient; Represents the end-to-end delay of the target transmission link; This represents the preset maximum allowable end-to-end delay threshold for the link; Represents the weighting coefficient of security events; The inversely normalized value of the historical security event occurrence rate of the target transmission link; The comprehensive security score is used for link priority ranking during the routing scheduling process.

[0009] Furthermore, after the raw data acquisition module completes data acquisition, it first uses a time window-based deduplication algorithm to perform redundancy filtering on the acquired multi-source heterogeneous data, then filters out abnormal flight data that exceeds the preset value range, then converts the remaining data into a unified structured transmission format, and then sends it to the nearest edge computing node through the communication module carried by the UAV. When the link signal strength is lower than the preset threshold, it automatically uses a seamless switching mechanism to switch to the backup communication link.

[0010] Furthermore, the pre-security verification module first performs identity verification on incoming drone data requests, matching the drone identity carried in the request with a whitelist of legitimate identities synchronously distributed in the cloud. If the match fails, the request is directly intercepted and the corresponding request source, request time, and request content are recorded. If the match is successful, access permission verification is performed, and the drone's operation type and operation range are combined to determine whether the drone has the access permission corresponding to the current data transmission request. After the access permission verification is passed, anomaly identification is performed on the request traffic, and unauthorized access behavior is identified by combining feature matching rules.

[0011] Furthermore, when the fragmentation encryption processing module performs fragmentation on the data to be transmitted, it first determines the size of each data fragment based on the total size of the data to be transmitted, the number of currently available transmission links, and the maximum transmission unit of the link. It then adds a corresponding fragmentation sequence number identifier and a total fragmentation number identifier to each data fragment. Finally, it performs symmetric encryption on the content of the data fragments using the independent encryption key that is effective for the corresponding fragment. After encryption, it generates a corresponding check value for each data fragment.

[0012] Furthermore, when the routing scheduling module performs path selection, it first filters out available transmission links with a comprehensive security score higher than a preset threshold. The threshold is dynamically adjusted according to business needs. Then, based on the current remaining bandwidth of each link, a weighted round-robin algorithm is used to allocate fragment transmission tasks of the corresponding size. During transmission, the status of each link is monitored in real time. If the comprehensive security score of a link is lower than the preset threshold, new transmission tasks are immediately stopped from being allocated to that link, and the remaining untransmitted fragments are reallocated to other compliant links. If a link is interrupted, the unfinished transmission tasks are automatically transferred.

[0013] Furthermore, this includes the following steps: The low-altitude UAV terminal collects multi-source operation data in real time through the raw data acquisition module. After completing redundancy filtering, anomaly removal and format regularization, it selects the edge computing node with the highest signal strength to access and send data. Edge computing nodes use a front-end security verification module to verify the identity of drones, verify permissions, and identify abnormal traffic, thus blocking requests that do not comply with security rules. Edge computing nodes use a fragmentation and encryption processing module to perform fragmentation and encryption processing on the verified data to be transmitted. Edge computing nodes select the optimal transmission path for each data fragment by combining the link comprehensive security score results with the routing scheduling module, and transmit the fragments to the cloud management and control platform in a multi-link parallel manner; The cloud-based management platform receives all data fragments through the aggregation and decryption module, performs integrity verification and retransmission to complete the data, and then decrypts and aggregates it to obtain the complete original data, which is then stored in the corresponding distributed database.

[0014] Furthermore, after receiving a data request from the drone, the edge computing node first uses the unified identity authentication module to call the public and private key pair corresponding to the blockchain identity identifier to complete two-way identity verification. Using a challenge-response mechanism, the edge node sends a random challenge code to the drone, and the drone signs the challenge code with its own private key and sends it back. The edge node uses the pre-stored drone public key to verify the signature. At the same time, the drone uses the same mechanism to verify the identity of the edge node. Only after both-way verifications are successful will the subsequent security verification process begin. If the identity of either party is invalid during the verification process, the interaction will be terminated directly, and an abnormal interaction log containing the identities of both parties, time, content, and reason for failure will be uploaded to the cloud management platform.

[0015] Furthermore, after the cloud-based management platform completes data aggregation and decryption, it matches the complete raw data with the preset business rules. For inspection-type operations, it matches the flight status threshold and sensor data threshold, while for surveying-type operations, it matches the data integrity requirements. If any abnormality is detected in the data, an early warning message is immediately generated. At the same time, the drone number, collection time, and collection location information corresponding to the abnormal data are pushed synchronously. All logs of the transmission process are permanently stored in the distributed log database in the cloud.

[0016] Compared with existing technologies, the beneficial effects of this invention are: This invention, by deploying a data sharding and multi-link parallel transmission mechanism at the edge, combined with routing and scheduling logic based on the comprehensive link status, can adapt to the transmission requirements of complex low-altitude communication environments, improve data transmission reliability, reduce latency fluctuations during transmission, support adjustments to scheduling strategies based on the transmission requirements of different services, and adapt to different types of low-altitude UAV operation scenarios. The edge side undertakes data preprocessing and redundancy filtering, reducing the amount of invalid data transmitted and lowering bandwidth consumption during transmission. When a single transmission link fails, the remaining data can be automatically switched to other suitable links to complete transmission, avoiding transmission interruption.

[0017] This invention deploys a two-way identity authentication mechanism across the entire chain, with a front-end security verification module at the edge to intercept unauthorized access requests and abnormal traffic, preventing abnormal traffic from reaching the cloud and reducing the security protection pressure on the cloud. The independent encryption of data shards and the dynamic key update mechanism reduce the risk of data leakage; the leakage of a single shard key will not affect the security of the entire data set. Each data shard is assigned an independent integrity verification identifier, which can promptly identify tampered data shards and trigger retransmission, preventing invalid or tampered data from entering subsequent processing flows and improving the security protection capabilities across the entire chain.

[0018] This invention offloads computational tasks such as security verification and encrypted data sharding to the edge, reducing computational pressure and bandwidth consumption in the cloud and supporting simultaneous data transmission by large-scale drone swarms. Unified retention of end-to-end transmission logs supports full-process tracing after a security incident, meeting the security auditing needs of various operational scenarios. The transmission architecture of this invention is compatible with multiple types of communication links and can dynamically adjust security protection levels and transmission scheduling strategies according to business needs, adapting to low-altitude drone operation scenarios with different security levels and transmission rate requirements, demonstrating high scenario adaptability. Attached Figure Description

[0019] Figure 1 This is a schematic block diagram of the overall flowchart of the UAV data security transmission system proposed in this invention; Figure 2 This is a schematic block diagram of the process for collecting and organizing raw data from unmanned aerial vehicles (UAVs) as proposed in this invention. Figure 3 This is the logic diagram of edge-side security verification and fragmented encryption proposed in this invention; Figure 4 This is a block diagram of routing scheduling and link security assessment proposed in this invention; Figure 5 This is a flowchart of the cloud-based aggregation decryption and operation auditing process proposed in this invention. Detailed Implementation

[0020] 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.

[0021] Reference Figures 1 to 5 A low-altitude unmanned aerial vehicle (UAV) data security transmission system based on edge computing includes a unified identity authentication module, a raw data acquisition module, a pre-security verification module, a fragmented encryption processing module, a routing scheduling module, and an aggregation decryption module, wherein: A unified identity authentication module is deployed across the entire data transmission chain, assigning unique and immutable identity identifiers to drones, edge computing nodes, and cloud management platforms based on blockchain. For example, identity information is stored on the consortium blockchain in the form of ledger entries, and the identity data is solidified using the commonly used PBFT consensus mechanism in consortium blockchains, making it tamper-proof once stored on the blockchain.

[0022] The raw data acquisition module is deployed on the low-altitude UAV terminal to collect UAV flight status data, airborne sensor operation data and positioning data in real time. The acquisition frequency is adjusted according to the operation type, redundancy filtering and format regularization are performed on the collected data, and the processed data is sent to the edge computing node cluster. For example, it can be sent to the nearest edge computing node through the preferred communication link. The pre-security verification module is deployed on an edge computing node cluster. Based on the identity identifiers and permission rules generated by the unified identity authentication module, it performs identity legitimacy verification, access permission verification, and abnormal traffic identification on all data requests sent by the access drone. Abnormal traffic identification can be driven by machine learning, intercepting illegal requests that do not comply with security rules and generating complete security logs that are uploaded to the management platform. For example, the abnormal traffic identification model can be trained offline based on historical abnormal traffic samples, and after going online, it can identify injected abnormal data packets by matching a feature library.

[0023] The fragmentation encryption processing module is deployed in the edge computing node cluster. It performs dynamic fragmentation processing on the data to be transmitted that has passed the security verification. It uses a symmetric encryption algorithm, such as the national cryptographic SM4 algorithm, to configure an independent verification identifier and encryption key for each data fragment. The routing and scheduling module is deployed on the edge computing node cluster. It obtains encrypted fragments output by the fragment encryption processing module, acquires the real-time network link status based on the SDN architecture, and selects the optimal transmission path for each data fragment by comprehensively considering the edge node load status, transmission link bandwidth resources, and link latency data, thereby achieving parallel transmission of encrypted fragments across multiple links. For example, the SDN controller collects real-time bandwidth, packet loss, and latency metrics through the network ports of each edge node, with a collection period of 1 second.

[0024] The aggregation and decryption module is deployed on a cloud management platform. It receives all data fragments transmitted in parallel, performs decryption and aggregation operations after verifying the integrity of the fragments, supports breakpoint resumption and fragment retransmission, restores the complete original transmitted data, and stores it in the corresponding distributed database.

[0025] In this invention, the low-altitude UAV data security transmission system based on edge computing may also include a dynamic key update module. Based on the data sensitivity level, the current transmission link security status, and the preset update cycle, the key used by the segmented encryption processing module is dynamically updated. For example, the key update cycle for the most sensitive classified data corresponding to a single segment can be 5 minutes, and the key update cycle for a single segment of ordinary operation data can be 1 hour. Each updated key is only effective for the corresponding newly generated data segment. The key update process adopts an encrypted and secure synchronous distribution method to complete the key synchronization between the edge node and the cloud. The key is generated by a hardware true random number generator.

[0026] In this invention, the low-altitude UAV data security transmission system based on edge computing may further include a link security assessment module, which performs real-time assessment of the comprehensive status of all available transmission links. The calculation logic of the comprehensive link security score during the routing scheduling process satisfies the following formula: ;in, The overall security score representing the target transmission link is a dimensionless value. This represents the bandwidth weighting coefficient, with a value ranging from 0 to 1. The normalized value of the available bandwidth of the target transmission link is a dimensionless ratio, ranging from 0 to 1. This represents the packet loss rate weighting coefficient, with a value ranging from 0 to 1. Represents the packet loss rate of the target transmission link. It is a dimensionless ratio with a value ranging from 0 to 1. This represents the delay weighting coefficient, with a value ranging from 0 to 1. Represents the end-to-end delay of the target transmission link, in milliseconds; This represents the preset maximum allowable end-to-end latency threshold for the link, in milliseconds. The value is determined based on the business scenario. hour, The value is 0; This represents the weighting coefficient for security events, with a value ranging from 0 to 1. The inversely normalized value of the historical security event occurrence rate of the target transmission link is a dimensionless ratio, ranging from 0 to 1. The score is in the range of 0 to 1. The comprehensive security score is used to prioritize links during the routing process. The weight coefficient is dynamically adjusted according to business needs. In security-priority scenarios, the weight coefficient of security events is increased, and in rate-priority scenarios, the weight coefficient of bandwidth is increased.

[0027] In this invention, after the original data acquisition module completes data acquisition, it first uses a time window-based deduplication algorithm to perform redundancy filtering on the acquired multi-source heterogeneous data. Then, it filters out abnormal flight data that exceeds the preset value range, converts the remaining data into a unified structured transmission format, and sends it to the nearest edge computing node through the communication module carried by the UAV. When the link signal strength is lower than the preset threshold, it automatically uses a seamless switching mechanism to switch to the backup communication link.

[0028] For example, for sensing parameters with slow-changing rates such as ambient temperature and humidity, line temperature, and atmospheric pressure, only the last valid sample value is retained within a 1-second sliding time window, and duplicate redundant data within the same window is eliminated, which can reduce the amount of invalid data transmission by more than 30%. Then, a dual verification mechanism combining the 3σ statistical criterion and hard thresholds is used to filter out abnormal data: first, the mean μ and standard deviation σ are calculated based on the historical normal operation samples of each type of data. Outliers falling outside the interval [μ-3σ, μ+3σ] are identified as outliers and eliminated. At the same time, preset hard threshold boundaries for various types of data (such as flight altitude, flight speed, and the range of airborne sensors) are superimposed. The dual verification ensures that abnormal flight data and abnormal sensing data are completely filtered out. Finally, the remaining data is converted into a unified structured JSON transmission format.

[0029] Each normalized data point is given a unique millisecond-level Unix collection timestamp and a drone blockchain identity. The data is then sent to the nearest edge computing node via the drone's multi-mode communication module. During data transmission, 5G or WiFi 6 high-speed communication links are prioritized. The preset signal strength trigger threshold for the 5G / WiFi 6 link is -85dBm. When the main link signal strength is detected to be lower than this threshold for three consecutive samplings (sampling interval of 100ms), a seamless switching mechanism with dual-link parallel buffering is automatically adopted to switch to the LoRa backup communication link. The LoRa link operates in the 433MHz industrial unlicensed frequency band and uses direct-sequence spread spectrum communication technology. The maximum line-of-sight transmission distance can reach 5km. During the switching process, the LoRa link is pre-connected and data buffered and synchronized before the main link is disconnected to ensure zero data loss during the switching process and to ensure the continuity of data transmission in complex low-altitude environments such as building obstruction and weak signal in mountainous areas.

[0030] In this invention, the pre-security verification module first performs identity verification on incoming drone data requests. It matches the drone identity carried in the request with a whitelist of legitimate identities synchronously distributed in the cloud. If the match fails, the request is directly intercepted and the corresponding request source, request time, and request content are recorded. If the match is successful, access permission verification is performed. It determines whether the drone has the access permission corresponding to the current data transmission request by combining the drone's operation type and operation range. After the access permission verification is passed, anomaly identification is performed on the request traffic. It identifies common illegal access behaviors such as SQL injection (e.g., request parameters carrying injection keywords such as UNION and SELECT) and Trojan injection (e.g., data packets with embedded malicious execution scripts or remote control command characteristics) by combining feature matching rules. If the traffic rate exceeds the preset threshold or a data packet with abnormal injection characteristics is detected, the corresponding traffic is directly intercepted. The logs of all interception operations are uploaded to the security control center of the cloud management platform in real time and trigger alarm push.

[0031] In this invention, when the fragmented encryption processing module performs fragmentation on the data to be transmitted, it first determines the size of each data fragment based on the total size of the data to be transmitted, the number of currently available transmission links, and the maximum transmission unit of the link. The fragment size ranges from one thousand bytes to ten megabytes and is smaller than the maximum transmission unit of the link. A corresponding fragment sequence number identifier and a total fragment number identifier are added to each data fragment. Then, the content of the data fragment is symmetrically encrypted using the independent encryption key that is effective for the corresponding fragment. After encryption, a corresponding check value, such as an MD5 check value, is generated for each data fragment. The check value is appended to the header of the data fragment to facilitate subsequent integrity verification in the cloud. The encryption key is only stored in the encrypted storage area of ​​the edge node and the cloud and is not transmitted with the data fragments.

[0032] In this invention, when the routing scheduling module performs path selection, it first filters out all available transmission links with a comprehensive security score higher than a preset threshold. The threshold is dynamically adjusted according to business needs. In high-security scenarios, the threshold is set to 0.8, selecting only the top 20% of high-quality links. Then, based on the current remaining bandwidth of each link, a weighted round-robin algorithm is used to allocate fragmented transmission tasks of corresponding sizes. Links with higher bandwidth are allocated larger total fragment sizes. During transmission, the status of each link is monitored in real time, for example, once per second. If the comprehensive security score of a link is lower than the preset threshold, new transmission tasks are immediately stopped from being allocated to that link, and the remaining untransmitted fragments are reallocated to other compliant links. If a link is interrupted, the unfinished transmission tasks are automatically transferred.

[0033] This invention also provides a method for secure data transmission of low-altitude unmanned aerial vehicles (UAVs) based on edge computing, applied to the aforementioned secure data transmission system for low-altitude UAVs based on edge computing. The method includes the following steps: The low-altitude UAV terminal collects multi-source operation data in real time through the raw data acquisition module. After completing redundancy filtering, anomaly removal and format regularization, it selects the edge computing node with the highest signal strength to access and send data. Edge computing nodes complete drone identity verification, permission verification, and abnormal traffic identification through a front-end security verification module, intercept all requests that do not comply with security rules, and generate and upload security logs. The edge computing node performs fragmentation and encryption processing on the verified data to be transmitted through the fragmentation and encryption processing module, and adds a unique sequence number and integrity verification identifier to each fragment. Edge computing nodes select the optimal transmission path for each data fragment by combining the link comprehensive security score results with the routing scheduling module, and transmit the fragments to the cloud management and control platform in a multi-link parallel manner; The cloud-based management platform receives all data fragments through the aggregation and decryption module, performs integrity verification and retransmission to complete the data, and then decrypts and aggregates it to obtain the complete original data, which is then stored in the corresponding distributed database.

[0034] In this invention, after receiving a data request from a drone, the edge computing node first uses a unified identity authentication module to call the public and private key pair corresponding to the blockchain identity identifier to complete two-way identity verification. A challenge-response mechanism is adopted, whereby the edge node sends a random challenge code to the drone, the drone signs the challenge code with its own private key and sends it back, and the edge node verifies the signature using the pre-stored drone public key. At the same time, the drone uses the same mechanism to verify the identity of the edge node. Only after both-way verifications are successful will the subsequent security verification process begin. If the identity identifier of either party is invalid during the verification process, the interaction will be terminated directly, and an abnormal interaction log containing the identities of both parties, time, content, and reason for failure will be uploaded to the cloud management platform.

[0035] In this invention, after the cloud-based management platform completes data aggregation and decryption, it matches the complete original data with preset business rules. For inspection-type operations, it matches flight status thresholds and sensor data thresholds; for surveying-type operations, it matches data integrity requirements. If any data anomalies are detected, an early warning message is immediately generated and pushed to the corresponding management personnel's terminals through multiple channels, including SMS, system notifications, and emails. At the same time, the drone number, collection time, and collection location information corresponding to the abnormal data are also pushed synchronously, facilitating management personnel to quickly locate the anomaly. All logs of the transmission process are permanently stored in a distributed log database in the cloud, meeting the needs of subsequent security audits and problem tracing. The storage capacity can be dynamically expanded to adapt to the needs of massive log storage.

[0036] The following two examples further illustrate the specific implementation of this system: The low-altitude UAV data security transmission system and method based on edge computing disclosed in this invention first completes the identity initialization of all nodes during actual deployment. The cloud management platform takes the lead in building a consortium blockchain network to assign a unique and tamper-proof identity identifier to all UAVs, edge computing nodes, and cloud functional modules participating in the operation. All identity identifiers are synchronously stored in the consortium blockchain nodes and the full-link identity whitelist. All subsequent interactive operations in the full link must complete identity verification.

[0037] The raw data acquisition module presets the acquisition frequency according to the job type: five times per second for inspection jobs, twice per second for surveying jobs, and eight times per second for emergency jobs. After acquisition, a one-second time window deduplication algorithm is first used to filter out duplicate and invalid data. Then, based on the preset normal range for each data type, abnormal data is removed using the 3σ criterion. Finally, all data is converted into a unified JSON format, and after attaching the acquisition timestamp and UAV identification, an access request is sent to the nearest edge computing node. The edge computing node cluster deploys an SDN controller, which collects the status information of all available transmission links in the entire network once per second, and synchronously completes the comprehensive security score calculation for each link. The routing scheduling process selects links based on the comprehensive score results.

[0038] The data fragmentation encryption module uses the CBC mode of the national cryptographic SM4 algorithm to complete the data fragmentation encryption. The dynamic key update module sets the key update cycle according to the data sensitivity level. The update cycle for classified data is five minutes, and the update cycle for ordinary operation data is one hour. The key synchronization adopts an encrypted and secure synchronous distribution method to complete the synchronization between edge nodes and the cloud. The key generation uses a hardware true random number generator to ensure that the key is unpredictable.

[0039] The pre-security verification module incorporates an abnormal traffic identification model trained on historical traffic samples, capable of recognizing common anomaly injections and forged request access. Logs of all intercepted operations are synchronously uploaded to the cloud management platform for permanent storage. Upon receiving data fragments, the cloud aggregation and decryption module first verifies the integrity check value. For fragments with missing or failed verification, retransmission is triggered. After receiving all fragments, decryption and aggregation yield the complete original data. Matching this data to corresponding business rules completes anomaly identification and alert push notifications. Logs of all transmission processes are stored in a distributed log database to support security auditing and tracing.

[0040] Example 1

[0041] This operation, applied to the inspection of overhead power lines in a provincial power grid, deployed 120 fixed-wing inspection drones, covering 300 kilometers of high-voltage overhead lines. An edge computing cluster was formed by deploying one edge computing node at each of the 35 substations along the line, and the cloud management platform was deployed on a private cloud server within the power grid. All drones, edge computing nodes, and cloud management modules completed identity registration before the operation began, and all identity information was synchronously stored in the consortium blockchain and the full-link identity whitelist. As this operation was a high-security, confidential operation, the key update cycle was set to five minutes, the link scoring threshold for the routing and scheduling process was set to 0.8, and the weighting coefficient was adjusted so that security events had the highest weighting.

[0042] After takeoff, the drone flies along a preset inspection route, collecting flight attitude data, high-definition image data of towers, line temperature sensor data, and positioning data in real time. The collection frequency is set to five times per second. After collection, the drone first filters out duplicate line temperature data using a one-second time window deduplication algorithm, and then removes abnormal flight data that exceeds the operating altitude range using the 3σ criterion. All remaining data is converted into a unified JSON format, and after attaching the collection timestamp and the drone's own identification, it scans the signal strength of surrounding communication links. It prioritizes the 5G communication link to connect to the nearest substation edge computing node. If the 5G signal strength is lower than a preset threshold, it automatically switches to the LoRa backup communication link. The switching process adopts a seamless switching mechanism to prevent data loss.

[0043] After receiving the access request from the drone, the edge computing node first initiates a two-way identity verification process. The edge computing node sends a randomly generated challenge code to the drone. The drone signs the challenge code using its stored private key and sends it back to the edge computing node. The edge computing node then uses the pre-stored corresponding drone public key to complete the signature verification. At the same time, the drone uses the same mechanism to send a challenge code to the edge computing node to complete the edge node identity verification. The entire verification process takes no more than fifty milliseconds and does not generate any additional transmission overhead.

[0044] After the two-way verification is successful, the pre-security verification module matches the drone's identity with the legal identity whitelist synchronized in the cloud. If the match is successful, the access permissions of the drone are further verified to confirm that the drone's operating range and data transmission permissions are consistent with the current request content. Then, the abnormal traffic identification model is called to detect the request traffic, identify and block abnormal data packets with SQL injection and Trojan injection characteristics. The logs of all interception operations are uploaded to the security control center of the cloud management platform in real time to trigger alarms.

[0045] Data to be transmitted that has passed security verification enters the fragmented encryption process. The total amount of data collected by a single UAV in a single inspection operation is about two gigabytes. There are currently four available transmission links for the edge node, and the maximum transmission unit of each link is 1,500 kilobytes. Therefore, the data fragment size is set to one megabyte, which is less than the transmission requirement of the maximum transmission unit of the link. Each data fragment is attached with a corresponding fragment sequence number and a total fragment count identifier. The fragment content is encrypted using the national cryptographic SM4 key that is effective in the current period. After encryption, a corresponding MD5 checksum is generated for each fragment and attached to the fragment header. The key is only stored in the encrypted storage area between the edge node and the cloud and is not transmitted with the fragments.

[0046] The routing scheduling module obtains the comprehensive security score of all available links from the SDN controller, selects three high-quality links with a score higher than 0.8, and allocates fragmented transmission tasks according to the remaining bandwidth of each link using a weighted round-robin algorithm. Links with higher bandwidth are allocated more fragments. During transmission, the status of each link is monitored once per second. If the comprehensive security score of a link is lower than 0.8, new transmission tasks are immediately stopped from being allocated to that link, and the remaining untransmitted fragments are reallocated to other qualified links. If a link is interrupted, the unfinished transmission tasks are automatically transferred to other available links.

[0047] The cloud-based management platform's aggregation and decryption module receives all transmitted data fragments. It first verifies the MD5 checksum of each fragment, triggering retransmission requests for fragments that fail verification or are missing. After all fragments are received, the corresponding period's key is used to decrypt them. Data is then aggregated according to the fragment sequence number to obtain complete raw inspection data, which is stored in the power grid's distributed database. The cloud-based management platform matches the raw inspection data with preset power grid inspection business rules. After identifying issues such as tower cracks and abnormal line temperatures, the platform pushes the data to the corresponding inspection management personnel's terminals via multiple channels including SMS, system notifications, and email. Simultaneously, it pushes the corresponding drone number, collection time, and collection location information for the abnormal data, facilitating rapid problem location by management personnel. All logs for this operation's transmission process are permanently stored in the cloud-based distributed log database, which can be retrieved at any time for security auditing and problem tracing.

[0048] Example 2

[0049] This operation, applied to emergency rescue scenarios for geological disasters in mountainous areas, deployed a total of thirty multi-rotor rescue drones, covering an area of ​​120 square kilometers. A temporary rescue command center deployed eight portable edge computing nodes to form an edge computing cluster, and the cloud management platform was deployed on the emergency management department's public cloud server. All drones, edge computing nodes, and cloud management modules completed identity registration before the operation began, and all identity information was synchronously stored in the consortium blockchain and the full-link identity whitelist. As this was a typical operation with high real-time requirements, the key update cycle was set to one hour, the link scoring threshold for the routing scheduling process was set to 0.5, and the weighting coefficient was adjusted to prioritize bandwidth.

[0050] After takeoff, the drone flies along a preset search and rescue route, collecting real-time high-definition image data, location data of trapped personnel, environmental temperature and humidity data, toxic gas concentration data, and flight status data. The collection frequency is set to eight times per second. After collection, the drone first filters out duplicate environmental temperature and humidity data using a one-second time window deduplication algorithm, and then removes abnormal sensor data that exceeds the normal range using the 3σ criterion. All remaining data is converted into a unified JSON format, and after attaching a collection timestamp and the drone's own identification, it scans the signal strength of surrounding communication links. It prioritizes connecting to the nearest portable edge computing node via a WiFi 6 communication link. If the WiFi 6 signal strength is lower than a preset threshold, it automatically switches to a LoRa backup communication link. The switching process employs a seamless switching mechanism to prevent data loss. For example, the drone is equipped with a multi-mode integrated communication module with a built-in protocol conversion unit to achieve buffering, forwarding, and seamless switching between different communication protocols such as 5G / WiFi 6 and LoRa.

[0051] After receiving the access request from the drone, the edge computing node first initiates a two-way identity verification process. The edge computing node sends a randomly generated challenge code to the drone. The drone signs the challenge code using its stored private key and sends it back to the edge computing node. The edge computing node then uses the pre-stored corresponding drone public key to complete the signature verification. At the same time, the drone uses the same mechanism to send a challenge code to the edge computing node to complete the edge node identity verification. The entire verification process takes no more than fifty milliseconds and does not generate any additional transmission overhead.

[0052] After the two-way verification is successful, the pre-security verification module matches the drone's identity with the legal identity whitelist synchronized in the cloud. If the match is successful, the access permissions of the drone are further verified to confirm that the drone's operating range and data transmission permissions are consistent with the current request content. Then, the abnormal traffic identification model is called to detect the request traffic, identify and block abnormal data packets with content tampering or forged request characteristics. The logs of all interception operations are uploaded to the security control center of the cloud management platform in real time to trigger alarms.

[0053] Data to be transmitted that has passed security verification enters the fragmented encryption process. The total amount of data collected by a single drone in a single search and rescue operation is about 800 megabytes. There are currently six available transmission links at the edge node, and the maximum transmission unit of each link is 1,500 kilobytes. Therefore, the data fragment size is set to 512 kilobytes. This value is less than the transmission requirement of the maximum transmission unit of the link. Each data fragment is attached with a corresponding fragment sequence number and a total fragment count identifier. The fragment content is encrypted using the national cryptographic SM4 key that is in effect in the current period. After encryption, a corresponding MD5 checksum is generated for each fragment and attached to the fragment header. The key is only stored in the encrypted storage area between the edge node and the cloud and is not transmitted with the fragments.

[0054] The routing scheduling module obtains the comprehensive security score of all available links from the SDN controller, selects five available links with a score higher than 0.5, and allocates fragmented transmission tasks according to the remaining bandwidth of each link using a weighted round-robin algorithm. Links with higher bandwidth are allocated more fragments. During transmission, the status of each link is monitored once per second. If the comprehensive security score of a link is lower than 0.5, new transmission tasks are immediately stopped from being allocated to that link, and the remaining untransmitted fragments are reallocated to other qualified links. If a link is interrupted due to mountainous terrain, the unfinished transmission tasks are automatically transferred to other available links.

[0055] The cloud-based management platform's aggregation and decryption module receives all transmitted data fragments. It first verifies the MD5 checksum of each fragment, triggering retransmission requests for fragments that fail verification or are missing. After all fragments are received, the corresponding period's key is used to decrypt them. Data is then aggregated according to the fragment sequence number to obtain complete raw rescue data, which is stored in the emergency management department's distributed database. The cloud-based management platform matches the raw rescue data with pre-defined emergency rescue business rules. After identifying issues such as the location of trapped personnel or excessive toxic gas concentrations, it pushes the data to the terminals of the corresponding rescue commanders via multiple channels, including SMS, system notifications, and email. Simultaneously, it pushes the drone number, collection time, and collection location information corresponding to the abnormal data, facilitating rapid deployment of rescue resources by commanders. All logs from this operation's transmission process are permanently stored in a distributed log database in the cloud, which can be retrieved at any time for security audits and problem tracing.

[0056] The operation process of the above embodiments intuitively demonstrates the practical application value of this solution. The edge side undertakes computational tasks such as data preprocessing, security verification, and encrypted fragmentation, effectively reducing the computational pressure and bandwidth consumption in the cloud and supporting multiple drones to simultaneously access and complete data transmission. The multi-link parallel transmission and dynamic scheduling mechanism adapts to the transmission needs of complex low-altitude communication environments, reducing packet loss and latency fluctuations during transmission and avoiding transmission interruptions caused by single-link failures. Security protection mechanisms such as end-to-end bidirectional identity verification, independent fragmentation encryption, and abnormal traffic interception effectively reduce security risks such as data leakage, content tampering, and unauthorized access, ensuring the integrity and confidentiality of transmitted data. This solution can dynamically adjust transmission strategies and security protection levels according to the needs of different services, adapting to the actual needs of various low-altitude drone operation scenarios. The end-to-end log retention mechanism meets the requirements of security auditing and problem tracing, possessing high practical value.

[0057] Reference Figure 2This diagram details the raw data processing logic on the drone side. To ensure the quality and transmission efficiency of uploaded data, the acquisition module first integrates heterogeneous information from multiple sources and introduces a time-window-based deduplication algorithm. To address jitter interference during flight, the system uses statistical criteria to filter abnormally fluctuating flight data, ensuring the accuracy of the data entering the database. The processed data is uniformly converted to standard JSON format and encapsulated with a specific timestamp and unique identifier. Regarding communication link selection, the system has an intelligent switching mechanism, prioritizing high-speed 5G or WiFi 6 links by default. When the current signal strength is detected to have attenuated below a threshold, the system automatically activates a seamless switching process, switching to a long-distance LoRa backup link to maintain communication, ensuring continuous data transmission in complex low-altitude environments.

[0058] Reference Figure 3 This diagram highlights the security measures implemented by edge nodes for accessing data. Adhering to the zero-trust principle, the system first initiates a challenge-response verification process through the unified identity authentication module, utilizing blockchain identity identifiers to complete two-way authentication between the edge node and the drone. After successful authentication, the pre-security verification module further performs access permission verification and machine learning-based abnormal traffic identification, effectively intercepting abnormal access behavior. For legitimate data, the fragmentation encryption module dynamically segments the data based on the maximum transmission unit of the current link and simultaneously calls the dynamic key update module to obtain the latest key. Each data fragment is encrypted using the national standard SM4 algorithm and appended with an independent sequence number and integrity check value. This fragmentation encryption mechanism not only increases the difficulty of cracking but also lays the foundation for subsequent multi-link concurrent transmission.

[0059] Reference Figure 4 This diagram illustrates how the routing scheduling module achieves intelligent path selection for data fragmentation. Based on a software-defined network architecture, the system monitors the status of all available transmission links across the network in real time. The link security assessment module comprehensively considers available bandwidth, packet loss rate, end-to-end latency, and historical security records to calculate a real-time comprehensive security score for each link. The routing scheduling module selects high-quality links that meet the score criteria based on preset service scenario priorities and uses a weighted round-robin algorithm to allocate fragmentation tasks in proportion to the link's bandwidth capacity. During transmission, the system maintains high-frequency monitoring once per second. If a link's status deteriorates or is interrupted, the system immediately executes task transfer logic, reassigning the remaining fragments to other secure links, thereby achieving a dynamic balance between load balancing and transmission reliability.

[0060] Reference Figure 5This diagram illustrates the restoration and value-added processing flow of data after it arrives at the cloud-based management platform. The aggregation and decryption module first summarizes data fragments from different paths. The system performs rigorous integrity checks on each fragment, automatically initiating retransmission requests for missing or corrupted fragments. Once all fragments are collected, the system uses synchronized keys to perform decryption and aggregation restoration. The restored raw data undergoes real-time inspection by the business rule matching module: if incomplete mapping data or excessive inspection data is detected, the system will immediately trigger an alarm. Finally, all business data and various security logs and operation records generated during transmission are permanently stored in a distributed log database, providing end-to-end traceability support for administrators and ensuring the manageability, controllability, and traceability of low-altitude UAV operations.

[0061] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An edge-computing-based low-altitude unmanned aerial vehicle data security transmission system, characterized in that, It includes a unified identity authentication module, a raw data acquisition module, a pre-security verification module, a fragmented encryption processing module, a routing scheduling module, and an aggregated decryption module; among which, The unified identity authentication module is deployed across the entire data transmission chain, and uses blockchain to assign unique and tamper-proof identity identifiers to drones, edge computing nodes and cloud management platforms. The raw data acquisition module is deployed on the low-altitude UAV terminal to collect UAV flight status data, airborne sensor operation data and positioning data in real time. The acquisition frequency is adjusted according to the operation type, redundancy filtering and format normalization are performed on the collected data, and the processed data is sent to the edge computing node cluster. The front-end security verification module is deployed on the edge computing node cluster. Based on the identity identifier and permission rules generated by the unified identity authentication module, it performs identity legality verification, access permission verification and abnormal traffic identification on data requests from drones, and intercepts unauthorized requests. The data fragmentation encryption module is deployed in the edge computing node cluster. It performs dynamic fragmentation processing on the data to be transmitted that has passed the security verification and uses a symmetric encryption algorithm to configure an independent verification identifier and encryption key for each data fragment. The routing and scheduling module is deployed on the edge computing node cluster. It obtains the encrypted fragments output by the fragment encryption processing module, acquires the network link status in real time based on the SDN architecture, and performs multi-link parallel transmission of encrypted fragments by comprehensively considering edge node load, transmission link bandwidth and link latency data. The aggregation and decryption module is deployed on a cloud management platform. It receives all data fragments transmitted in parallel, performs decryption and aggregation operations after verifying the integrity of the fragments, and restores the complete original transmitted data. 2.The low-altitude unmanned aerial vehicle data security transmission system based on edge computing of claim 1, wherein, It also includes a dynamic key update module, which dynamically updates the independent keys corresponding to each shard according to the data sensitivity level, the current transmission link security status and the preset update cycle. The key update process uses an encrypted and secure synchronous distribution method to synchronize the shard key information between the edge node and the cloud. The key is generated by a hardware true random number generator. 3.The low-altitude unmanned aerial vehicle data security transmission system based on edge computing of claim 1, wherein, It also includes a link security assessment module, which performs real-time assessment of the overall status of all available transmission links. The calculation logic of the link comprehensive security score during route scheduling satisfies the following formula: ； in, A comprehensive security score representing the target transmission link; Represents the bandwidth weighting coefficient; Normalized value representing the available bandwidth of the target transmission link; Represents the packet loss rate weighting coefficient; Represents the packet loss rate of the target transmission link; Represents the delay weighting coefficient; Represents the end-to-end delay of the target transmission link; This represents the preset maximum allowable end-to-end delay threshold for the link; Represents the weighting coefficient of security events; The inversely normalized value of the historical security event occurrence rate of the target transmission link; The comprehensive security score is used for link priority ranking during the routing scheduling process.

4. The low-altitude unmanned aerial vehicle (UAV) data security transmission system based on edge computing according to claim 1, characterized in that, After the raw data acquisition module completes data acquisition, it first uses a time window-based deduplication algorithm to perform redundancy filtering on the acquired multi-source heterogeneous data, then filters out abnormal flight data that exceeds the preset value range, then converts the remaining data into a unified structured transmission format, and then sends it to the nearest edge computing node through the communication module on the UAV. When the link signal strength is lower than the preset threshold, it automatically uses a seamless switching mechanism to switch to the backup communication link.

5. The low-altitude unmanned aerial vehicle data security transmission system based on edge computing according to claim 1, characterized in that, The pre-security verification module first performs identity verification on incoming drone data requests, matching the drone's identity carried in the request with a whitelist of legitimate identities synchronously distributed in the cloud. If the match fails, the request is directly intercepted and the corresponding request source, request time, and request content are recorded. If the match is successful, access permission verification is performed, taking into account the drone's operation type and operation range to determine whether the drone has the access permissions corresponding to the current data transmission request. After the access permission verification is passed, anomaly identification is performed on the request traffic, and unauthorized access behavior is identified by combining feature matching rules.

6. The low-altitude unmanned aerial vehicle data security transmission system based on edge computing according to claim 1, characterized in that, When the fragmentation encryption processing module performs fragmentation on the data to be transmitted, it first determines the size of each data fragment based on the total size of the data to be transmitted, the number of currently available transmission links, and the maximum transmission unit of the link. It then adds a corresponding fragmentation sequence number identifier and a total fragmentation number identifier to each data fragment. Finally, it performs symmetric encryption on the content of the data fragments using the independent encryption key that is effective for the corresponding fragment. After encryption, it generates a corresponding check value for each data fragment.

7. The low-altitude unmanned aerial vehicle data security transmission system based on edge computing according to claim 3, characterized in that, When the routing scheduling module performs path selection, it first filters out available transmission links with a comprehensive security score higher than a preset threshold. The threshold is dynamically adjusted according to business needs. Then, based on the current remaining bandwidth of each link, a weighted round-robin algorithm is used to allocate fragment transmission tasks of the corresponding size. During transmission, the status of each link is monitored in real time. If the comprehensive security score of a link is lower than the preset threshold, new transmission tasks are immediately stopped from being allocated to that link, and the remaining untransmitted fragments are reallocated to other compliant links. If a link is interrupted, the unfinished transmission tasks are automatically transferred.

8. An edge computing-based low-altitude UAV data security transmission method applied to the edge computing-based low-altitude UAV data security transmission system of any one of claims 1-7, characterized in that, Includes the following steps: The low-altitude UAV terminal collects multi-source operation data in real time through the raw data acquisition module. After completing redundancy filtering, anomaly removal and format regularization, it selects the edge computing node with the highest signal strength to access and send data. Edge computing nodes use a front-end security verification module to verify the identity of drones, verify permissions, and identify abnormal traffic, thus blocking requests that do not comply with security rules. Edge computing nodes use a fragmentation and encryption processing module to perform fragmentation and encryption processing on the verified data to be transmitted. Edge computing nodes select the optimal transmission path for each data fragment by combining the link comprehensive security score results with the routing scheduling module, and transmit the fragments to the cloud management and control platform in a multi-link parallel manner; The cloud-based management platform receives all data fragments through the aggregation and decryption module, performs integrity verification and retransmission to complete the data, and then decrypts and aggregates it to obtain the complete original data, which is then stored in the corresponding distributed database. 9.The edge computing based low-altitude UAV data security transmission method according to claim 8, characterized in that, After receiving a data request from a drone, the edge computing node first uses the unified identity authentication module to call the public and private key pairs corresponding to the blockchain identity identifier to complete two-way identity verification. A challenge-response mechanism is adopted, whereby the edge node sends a random challenge code to the drone, the drone signs the challenge code with its own private key and sends it back, and the edge node verifies the signature using the pre-stored drone public key. At the same time, the drone uses the same mechanism to verify the identity of the edge node. Only after both-way verifications are successful will the subsequent security verification process begin. If the identity of either party is invalid during the verification process, the interaction will be terminated directly, and an abnormal interaction log containing the identities of both parties, time, content, and reason for failure will be uploaded to the cloud management platform. 10.The edge computing based low-altitude UAV data security transmission method according to claim 8, characterized in that, After the cloud-based management platform completes data aggregation and decryption, it matches the complete raw data with the preset business rules. For inspection-type operations, it matches the flight status threshold and sensor data threshold, while for surveying-type operations, it matches the data integrity requirements. If any abnormality is detected in the data, an early warning message is immediately generated. At the same time, the drone number, collection time, and collection location information corresponding to the abnormal data are pushed synchronously. All logs of the transmission process are permanently stored in the distributed log database in the cloud.

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