A drone collaborative method based on blockchain and three-phase encryption algorithm

Abstract

This invention relates to a drone collaboration method based on blockchain and a three-phase encryption algorithm, belonging to the field of drone technology. The method includes: constructing a temporary task group based on the regional dynamic cross-chain digital identity credentials of each drone; distributing a dynamic task code specific to this task within the task group based on a confirmation decision node; responding to a collaborative perception request, drones within the task group perform multi-source collaborative perception and cross-verification of abnormal targets based on the code, and generate a threat assessment result; the decision node generates a signed security operation instruction based on a consensus mechanism and schedules the target drone to execute collaborative countermeasures; finally, key event data throughout the task process is recorded on the blockchain, and the dynamic reputation value of the drones is updated accordingly. This application realizes rapid self-organization, self-optimization grouping, trusted collaborative perception, consensus decision-making, and precise countermeasures for drone swarms under decentralized scheduling, and ensures the auditability and traceability of the entire process.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a UAV collaborative method based on blockchain and a three-phase encryption algorithm. Background Technology

[0002] In recent years, with the rapid development and widespread application of unmanned aerial vehicle (UAV) technology, scenarios such as urban air traffic management (UAM), large-scale logistics delivery, and regional collaborative monitoring are becoming a reality. In these scenarios, airspace will become increasingly congested, and UAV swarms from different operators with different missions will need to share the same airspace. Ensuring that these heterogeneous UAV swarms can operate safely, efficiently, and orderly in dense and dynamic airspace environments, and possess the ability to cope with security threats such as unauthorized flights, deception, or malicious interference, is a core challenge facing next-generation air traffic control systems and autonomous collaborative UAV technologies.

[0003] To ensure the safety and orderly operation of drone flights, existing technologies primarily employ two approaches. The first is a centralized management model, which involves establishing a regional drone command and control center. All legitimate drones must register at the center and report their real-time status during flight. The command center integrates multi-source information monitoring of the airspace, including radar and ADS-B, to uniformly identify drones, issue conflict warnings, and generate release commands for relevant drones. The central system typically maintains an independent database of all drone identities, flight logs, and command records. The second approach is a formation-based autonomous model, more commonly seen in specific industrial applications. A drone formation is defined before a mission, with one drone designated as the fixed command drone (leader) and the rest as controlled drones (wingmen). The formation uses pre-configured communication keys and formation identification codes. The leader drone is responsible for receiving external commands, calculating and generating sub-tasks within the formation, and distributing them to the wingmen for execution. The wingmen primarily communicate with the leader drone.

[0004] However, centralized architectures suffer from single-point-of-failure risks and struggle to achieve real-time identity trust and collaboration across operating entities. The fleet-based autonomous mode relies on fixed lead nodes, and its decision-making depends on single-point awareness, making it difficult to quickly mobilize resources across the entire fleet for multi-faceted, mutually verifiable collaborative verification of abnormal targets, resulting in insufficient efficiency and accuracy in threat identification. Furthermore, both modes lack a mechanism for recording the entire process of actions in a manner that allows multiple parties to witness it and ensures it is tamper-proof, hindering post-event auditing and accountability. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a drone collaboration method based on blockchain and three-phase encryption algorithm, aiming to solve at least one of the above-mentioned technical problems.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: This application provides a drone collaboration method based on blockchain and a three-phase encryption algorithm, employing the following technical solution: A drone collaboration method based on blockchain and three-phase encryption algorithm includes: A temporary task group is constructed based on the cross-chain digital identity credentials of multiple drones. The multiple drones are drones that enter the same collaborative airspace. The cross-chain digital identity credentials are generated and registered in the blockchain network. The cross-chain digital identity credentials include the verifiable attributes and dynamic reputation value of the drones. The verifiable attributes represent the physical identity, hardware capabilities and mission qualifications of the drones. The dynamic reputation value represents the behavior and contribution of the drones in historical collaborative tasks. Within the temporary task group, at least one decision node is identified from multiple drones based on a preset multidimensional dynamic scoring model. Within the temporary task group, based on a preset password generation algorithm and collaborative tasks, a dynamic task password associated with the collaborative tasks is generated and distributed to each UAV in the task group. The dynamic task password specifies the temporary identification signal, encryption algorithm, and communication protocol used by the UAV in the temporary task group. In response to a collaborative perception request for an abnormal target sent by any UAV within the temporary task group, based on dynamic task cryptography, multiple UAVs within the temporary task group are coordinated to perform multi-source collaborative perception and cross-verification of the abnormal target, generating a threat assessment result. The threat assessment results are sent to each of the decision nodes, so that each of the decision nodes generates a consensus-signed security operation instruction based on the consensus mechanism. Based on the security operation instructions and the dynamic task password, the target drone is identified, and the target drone is scheduled to perform corresponding coordinated countermeasures; and, Key event data generated during this collaborative task will be recorded on the blockchain network to trigger the blockchain to update the dynamic reputation value in the target drone's cross-chain digital identity credential based on the key event data.

[0007] The beneficial effects of this invention are as follows: By using blockchain-based cross-chain digital identity credentials, verifiable and trustworthy digital identities are established for drones from different management domains, enabling the construction of temporary task groups in open airspace without the intervention of a central authority, fundamentally solving the problem of mutual trust across management domains. Through dynamically generated passwords bound to tasks, an independent, temporary, and secure communication environment is provided for each collaborative task, effectively preventing the risks associated with long-term key exposure. Utilizing distributed sensing resources within the temporary task group, the accuracy of threat identification and assessment under complex air conditions is improved through multi-source information cross-verification and a swarm intelligence evaluation model. Finally, blockchain technology is used to immutably store key events throughout the entire process, forming a traceable airspace security ledger.

[0008] Based on the above technical solution, the present invention can be further improved as follows.

[0009] Furthermore, the construction of a temporary task group based on cross-chain digital identity credentials of multiple drones includes: Obtain cross-chain SBT identity credentials broadcast separately by multiple drones in the same collaborative airspace; Based on the cross-chain verification protocol, the validity of the SBT identity credential of each drone is verified to obtain a validity verification result, which includes valid SBT identity credentials and invalid SBT identity credentials. Based on verified and valid SBT identity credentials, consensus is reached among the multiple drones to construct a temporary task group; The formation information and member list of the temporary task group are recorded in the blockchain network; The registration method for the cross-chain SBT identity credential includes: Based on the three-phase encryption algorithm, an identity code for the drone is assigned, and the identity code for the drone is uploaded to the first blockchain to which the drone belongs; On the first blockchain to which the drone belongs, a digital identity credential for the drone is generated based on the drone's physical identity information, compliance credentials, and identity code. The target node of the first blockchain signs and endorses the initial attributes of the drone, generating a verifiable attribute declaration; Send the digital identity credential and the attribute declaration to the second blockchain; The second blockchain verifies the signature of the first blockchain, and after successful verification, generates a cross-chain SBT identity credential for the drone, wherein the cross-chain SBT identity credential includes the drone's identity digest, the verifiable attribute declaration, and an initialized dynamic reputation value.

[0010] The beneficial effects of adopting the above-mentioned further scheme are as follows: Using cross-chain verification protocols to efficiently and reliably verify the identities of drones from different first-level blockchains (such as chains from different manufacturers or operators) ensures the global credibility of the identities of task group members; by driving a decentralized consensus process based on verified identity credentials, drone clusters that are not affiliated with each other can quickly and spontaneously reach a consensus on task formation without a pre-set central node; the consensus results are recorded in the blockchain network in the form of transactions, establishing an immutable proof for this temporary collaboration, providing a trust anchor for the traceability of rights and responsibilities for all subsequent collaborative operations, and making the existence and status of this dynamic organization publicly verifiable to authorized nodes.

[0011] Furthermore, the three-phase encryption algorithm encrypts based on timestamps and ternary notation; the identity code is a static identity code generated by the three-phase encryption algorithm and burned into the drone chip, and the static identity code is unique and recorded on the first blockchain.

[0012] The beneficial effects of adopting the above-mentioned further scheme are as follows: By using a three-phase encryption algorithm based on timestamps and ternary notation, a unique and unforgeable identity code can be generated for the drone and burned into its chip. This static identity code is recorded on the first blockchain, becoming the basis for drone identity authentication. This identity code possesses uniqueness and security, providing reliable protection for drone identification and anti-counterfeiting, and also providing a cryptographic basis for the generation of subsequent dynamic mission passwords.

[0013] Furthermore, the blockchain network includes a main chain and secondary chains; The main chain consists of a data center and a command center, used to verify and store the static identity code and dynamic mission password of the drone; The secondary chain consists of an intermediary machine and a command center, and is generated according to the collaborative task, used to calculate and verify the dynamic task password; After the collaborative task is completed, all information of the secondary chain is uploaded to the main chain, and the secondary chain is deregistered. The individual nodes in the blockchain network consist of a command center, an intermediary machine, and a function machine. All individual nodes belong to the main chain. When a secondary chain is generated, the individual nodes join the corresponding secondary chain according to the scheduling information.

[0014] The beneficial effects of adopting the above-mentioned further solution are as follows: The blockchain network employs a structure combining a main chain and secondary chains. This allows for long-term storage of the drone's static identity information while simultaneously generating temporary secondary chains for specific collaborative tasks to perform dynamic task password calculation and verification. This multi-level chain structure separates identity verification from task execution, improving the flexibility and security of task processing. After the task is completed, the information from the secondary chain is uploaded to the main chain and deregistered, ensuring data integrity and efficient on-chain data updates, while avoiding the potential risks of the secondary chain existing indefinitely.

[0015] Furthermore, the process of identifying decision nodes from multiple drones based on a preset multidimensional dynamic scoring model includes: Obtain real-time status information of each UAV within the temporary task group, including computing resources, communication link quality, remaining energy, sensor payload type, topology stability, and dynamic reputation value; Each drone is given a first score based on its communication link quality, location, and topology stability. A second score for each drone is determined based on the degree of matching between the phase of the collaborative task and the sensor payload type of each drone, as well as the computing resources. A third score is determined for each drone based on its remaining energy, real-time power consumption, and predicted remaining flight time. A fourth score is determined for each drone based on its dynamic reputation value; Based on the stage and network status of the collaborative task, the weight information of multiple evaluation dimensions in the multidimensional dynamic scoring model is determined. Based on the weight information and the first, second, third, and fourth scores of each of the drones, at least one decision node is determined.

[0016] The beneficial effects of adopting the above-mentioned further scheme are as follows: by comprehensively considering multiple key dimensions such as the communication hub performance of nodes (communication link quality, location, topology stability), task execution adaptability (matching sensor payload, computing resources and task stage), continuous service capability (remaining energy and predicted endurance), and long-term behavioral reliability (dynamic reputation value), and dynamically adjusting the weight of each dimension based on the task stage and network conditions, the elected decision-making nodes are not only highly capable, but also matched with the needs of collaborative tasks, thereby improving the overall decision-making quality, response efficiency and adaptability of temporary task groups when facing different task stages, different threat types and different network conditions.

[0017] Furthermore, the step of generating and distributing dynamic task passwords associated with the collaborative task to each drone in the task group based on a preset password generation algorithm and collaborative task includes: Based on the task phase of the collaborative task, the decision node determines the target codebook type to be activated from a set of preset codebooks. Based on the target password type, the decision node generates dynamic task passwords corresponding to the temporary task group in real time using a three-phase encryption algorithm. The decision node distributes the generated dynamic task password to each drone in the temporary task group; The decision node communicates with each UAV according to the fixed-point communication time, decoding method and password change timestamp agreed upon by the dynamic task password; After the collaborative task is completed, all intermediary machines and feature machines in the same area will deregister the dynamic task password.

[0018] The beneficial effect of adopting the above-mentioned further scheme is that by intelligently selecting and generating a unique dynamic task password based on the real-time task stage by the decision node, it is ensured that each collaborative task has an independent, one-time password communication security environment.

[0019] Furthermore, it also includes: Based on the current parameters of the dynamic task password and the preset grouping algorithm, the UAVs in the temporary task group are divided into multiple hierarchical communication groups. Each group includes at least one intermediary machine and one function machine. The intermediary machine represents a node responsible for communicating with the upper layer within the group, and the function machine represents a node that communicates with the intermediary machine within the group. The role of the intermediary machine changes within its group according to the received encryption instructions. Within each group, an online intermediary machine communicates with the decision node. If the online intermediary machine fails, a new intermediary machine is replaced in the group where the failed intermediary machine is located according to a predetermined replacement rule. The functional machines in each group communicate with the intermediary machines in the group. When the intermediary machine communicates with the functional machines in this group, it obtains the authentication feedback of all functional machines in this group. If the authentication feedback of all functional machines is not obtained, the authentication of the intermediary machine fails. When intermediary machines in different communication groups communicate with each other, they exchange and verify the grouping credentials issued by the decision node. If the grouping credentials fail to be verified, the communication authentication fails.

[0020] The beneficial effects of adopting the above-mentioned further scheme are as follows: Using the parameters of the dynamic task cryptography as a generation factor, the drones within the temporary task group are automatically divided into multiple logically independent communication groups, and a changeable intermediary role is dynamically assigned within each group, thus forming an orderly multi-level command and communication link in a decentralized architecture. This greatly optimizes network bandwidth utilization, reduces the load and interference of direct communication between decision nodes and all terminal nodes, and improves the scalability and efficiency of communication in large-scale clusters by using intermediary machines for aggregation and distribution. Simultaneously, the dynamic transformation of the intermediary machine role and the mechanism of automatic replacement according to predetermined rules after failure ensure that the failure of a single node will not paralyze the communication of the entire group, effectively avoiding mass incapacity caused by the identification, interference, or damage of critical relay nodes.

[0021] Furthermore, it also includes: In response to the number of drones in the temporary task group reaching a first threshold, multiple intermediary drones are further grouped to form a higher-level intermediary cluster, constituting a swarm group. In the intermediary cluster, a superior intermediary machine is dynamically designated according to the encryption instructions, and the role of the superior intermediary machine changes randomly according to the different encryption instructions. In response to the spatial distance between two communication groups being less than a set threshold or their flight paths being similar, the two communication groups are automatically triggered to form an intermediate layer group to coordinate their communication and actions.

[0022] The beneficial effects of adopting the above-mentioned further scheme are: communication between the intermediary machine and the function machine requires authentication feedback from all group members; failure to do so is considered an authentication failure, thus preventing unauthorized nodes from interfering with the task execution process. Furthermore, during inter-group communication, group credentials issued by the decision node are exchanged and verified to ensure the legitimacy of both communicating parties' identities and prevent cross-group deception or identity forgery. This two-way authentication mechanism significantly improves the communication security and mission integrity of the UAV collaborative system.

[0023] Furthermore, prior to responding to a cooperative perception request for an abnormal target sent by any UAV within the temporary task group, a multi-source cooperative target acquisition step is also included: The system acquires radar information from the command system as a third-party source. When an incorrect identification signal is detected in the operational airspace, the system publishes the location information of the incorrect identification signal to the grouping intermediary and command system, and marks the corresponding object as abnormal. Obtain the airborne radar information of each UAV in the temporary task group. When the airborne radar detects additional or abnormal spatial locations, mark the corresponding objects as abnormal. Obtain the recognition results of the image recognition system of each UAV in the temporary task group. When the image recognition system detects a target outside the group, mark the corresponding object as abnormal. The communication signals in the airspace where the temporary task group is located are obtained. When an unconventional communication signal is detected, the abnormal signal source is identified and locked, and the corresponding object is marked as abnormal. Based on the anomaly marker, the collaborative perception request for the anomaly target is generated.

[0024] The beneficial effects of adopting the above-mentioned further scheme are: during inter-group communication, the role of the upper-level intermediary machine changes randomly according to encrypted instructions, meaning the upper-level structure possesses a certain degree of flexibility and dynamism. This mechanism enables the collaborative system to have higher adaptability and autonomous decision-making capabilities when facing complex tasks or unexpected situations. It not only effectively prevents attackers from locating or sabotaging the system through fixed roles, but also enhances the system's stability and survivability in uncertain environments, improving the actual effectiveness of UAV collaborative combat.

[0025] Furthermore, the method of coordinating multiple drones within a temporary task group based on dynamic task cryptography to perform multi-source collaborative perception and cross-verification of the abnormal target, generating threat assessment results, includes: Obtain a collaborative perception request sent by any UAV, wherein the collaborative perception request represents a request for dynamic task cryptographic encryption signature of the communication group to which the UAV belongs, and the collaborative perception request includes preliminary characteristic information of abnormal targets; Based on the collaborative sensing request and the real-time location, sensor payload type and remaining energy of each UAV in the task group, multiple UAVs participating in collaborative sensing are identified as task nodes. Based on the dynamic task password corresponding to each task node, encrypted concrete perception instructions are distributed to each task node so that each task node can perform a perception task and obtain a perception evidence package. Obtain the perception evidence packet returned by each of the task nodes, which is dynamically password-signed by itself. Spatiotemporal alignment and cross-validation are performed on the perceptual evidence of each task node to obtain the cross-validation results; Based on the results of cross-validation, the cross-chain digital identity credentials of the abnormal target queried from the blockchain network, and the preset threat assessment model, the threat assessment result is determined and a summary of the threat assessment result is recorded on the blockchain network. The threat assessment result includes the threat level and confidence level.

[0026] The beneficial effects of adopting the above-mentioned further scheme are as follows: By utilizing collaborative perception requests and perception evidence packages encrypted and signed with dynamic task cryptography, threat information is transferred within the temporary task group while ensuring that all interactive instructions and data sources are authentic and untampered with. By selecting task nodes and issuing specific perception instructions based on cryptographic encryption, distributed perception resources within the task group are mobilized to collaboratively detect the same abnormal target from multiple dimensions and perspectives. By performing spatiotemporal alignment and cross-verification on the perception evidence returned by each node, which includes time and location stamps, the system effectively identifies and eliminates false alarms, missed alarms, or deception by individual sensors, thereby improving the accuracy of threat detection and feature extraction.

[0027] Furthermore, each of the aforementioned decision nodes generates a consensus-signed secure operation instruction based on a consensus mechanism, including: For any decision node, after obtaining the threat assessment result, the decision node will be used as a proposal node and will generate candidate security operation instructions based on a preset hierarchical response strategy library. The proposal node broadcasts the candidate security operation instructions to all decision nodes in the temporary task group based on the high-level dynamic task password, whereby the high-level dynamic task password is a dynamic task password agreed upon between the decision nodes. For each decision node that obtains candidate security operation instructions, the obtained candidate security operation instructions are reviewed and voted on to obtain the voting results; The proposal node obtains the voting results of all decision nodes. If the number of "agree" votes in the voting results exceeds a preset threshold, it is determined that a consensus has been reached, and the candidate security operation instruction is determined as the final security operation instruction. Each decision node that votes in favor performs multi-signature on the final secure operation instruction based on its own private key, generating a consensus-signed secure operation instruction.

[0028] The beneficial effects of adopting the above-mentioned further scheme are as follows: through review and voting by multiple independent decision-making nodes, the instruction takes effect after obtaining more than a preset threshold of consent. After the instruction takes effect, all decision-making nodes that voted in favor use their respective private keys to multi-sign it, making the final generated secure operation instruction unforgeable. At the same time, by combining the consensus process with blockchain notarization, the voting results, final instructions and multi-signatures and other key evidence are completely recorded on the chain, making the entire decision-making chain completely transparent, auditable and tamper-proof.

[0029] Furthermore, the step of determining the target drone based on the security operation command and the dynamic task password, and scheduling the target drone to perform corresponding cooperative countermeasures, includes: Based on a preset signature verification method, the validity of the multi-digital signature on the secure operation instruction signed by consensus is verified. After successful verification, the security operation instructions are parsed to obtain the countermeasure strategy, expected effect and constraints, and the countermeasure strategy is decomposed into multiple sub-tasks. Based on the status information of each UAV in the temporary task group and the preset distributed scheduling optimization model, at least one optimal target UAV is matched for each subtask. The scheduling optimization model takes minimizing the overall task completion time, maximizing the success probability of execution, and balancing the UAV load as the objective function, and comprehensively considers the status information of each candidate UAV, the distance between the candidate UAV and the subtask location, the matching degree between the sensor and the payload and the subtask, and the dynamic reputation value for optimization calculation. A corresponding encrypted executable task package is generated for each target drone. The encrypted executable task package is encrypted based on the dynamic task password corresponding to the target drone and encapsulates the details of the assigned subtask, the collaborative time window, the action path planning, and the authorization credential fragment extracted from the consensus-signed secure operation instruction. The encrypted executable task package is sent to the corresponding target drone through the intermediary machine of the group to which each target drone belongs; For any of the target drones, after acquiring and decrypting the encrypted executable task package, the target drone verifies the validity of the authorization credential fragment encapsulated in the decrypted executable task package, and executes the sub-task within a set time window after the verification is successful. For any of the target drones, during the execution process, the target drone will transmit its execution status back after being encrypted and signed by the target drone's dynamic task password; Based on the returned execution status information, the execution progress of all subtasks is monitored, and the execution process is dynamically coordinated and conflict resolved according to preset rules.

[0030] The beneficial effects of adopting the above-mentioned further scheme are as follows: By performing multi-signature verification on the secure operation instructions signed by consensus, the legitimacy and collective authority of the countermeasures to be executed are ensured, eliminating the risk of execution of illegal or forged instructions. By dividing the countermeasure strategy into multiple sub-tasks and using a distributed scheduling optimization model aimed at efficiency, success rate, and load balancing, the optimal UAV execution unit is dynamically matched to each sub-task, achieving the adaptation of cluster resources and task requirements in the spatiotemporal dimensions, thereby maximizing the effectiveness of overall collaborative countermeasures.

[0031] Furthermore, it also includes cross-cluster authentication steps: When a cluster of drones or a single drone from outside the region enters the airspace of the current collaborative task, the command center on the main chain verifies the identity of the cluster of drones or the single drone from outside the region based on the identity information on the chain. After identity verification, depending on the command level and mission type, it is decided whether to add the drone cluster or individual drones outside the area into the command system of the temporary mission group. If you choose to join, the drone cluster or individual node corresponding to a single drone outside the area will be added to the secondary chain corresponding to the current collaborative task.

[0032] The beneficial effects of adopting the above-mentioned further scheme are: when two communication formations are spatially close or have similar flight paths, the intermediate-layer formation mechanism is automatically triggered, achieving efficient coordination and unified scheduling between formations. This mechanism not only improves the efficiency of multi-formation collaboration but also ensures logical consistency between communication and action, enabling seamless connection and collaborative operations between different formations. This automatic formation function greatly reduces human intervention and improves mission response speed and execution accuracy.

[0033] Furthermore, the construction of the temporary task group also includes a step for determining whether the feature phone can autonomously join: After receiving the collaborative task information, each feature phone obtains its own static identity code, function type, and distance information from the task target; Each feature phone independently determines whether to join the temporary task group based on its own static identity code, function type, and distance information; for feature phones that determine whether to join, their static identity code and dynamic task password are recorded on the blockchain network.

[0034] The beneficial effects of adopting the above-mentioned further scheme are as follows: Before the mission begins, the UAV swarm uses a multi-source collaborative target acquisition method, utilizing command system radar, airborne radar, image recognition systems, and communication signal identification to detect and mark targets within the airspace. When abnormal targets are detected (such as incorrectly identified signals, abnormal spatial locations, or unconventional communication signals), a collaborative perception request can be generated in a timely manner, and the abnormal targets can be immediately marked and tracked. This multi-source collaborative target acquisition mechanism significantly improves the mission swarm's ability to detect potential threats, ensuring accurate target identification and efficient response by UAVs in complex environments. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating a drone collaboration method based on blockchain and a three-phase encryption algorithm, provided as an embodiment of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0038] This application provides a drone collaboration method based on blockchain and a three-phase encryption algorithm. This method can be executed by an electronic device, which can be a server.

[0039] like Figure 1 As shown, a drone collaboration method based on blockchain and a three-phase encryption algorithm includes: S1. Based on the cross-chain digital identity credentials of multiple drones, a temporary task group is constructed. The multiple drones are drones that enter the same collaborative airspace. The cross-chain digital identity credentials are generated and registered in the blockchain network. The cross-chain digital identity credentials include the verifiable attributes and dynamic reputation value of the drones. The verifiable attributes represent the physical identity, hardware capabilities and task qualifications of the drones. The dynamic reputation value represents the behavior and contribution of the drones in historical collaborative tasks. In this embodiment, the cross-chain digital identity credential represents a digital identity certificate generated based on blockchain technology that can be verified across different blockchain systems. A temporary task group refers to a dynamically formed, time-sensitive drone collaborative group designed to complete specific collaborative tasks (such as area monitoring or coordinated countermeasures). Collaborative airspace refers to a range defined in both space and time.

[0040] Specifically, the construction of a temporary task group based on cross-chain digital identity credentials of multiple drones includes: Obtain cross-chain SBT identity credentials broadcast separately by multiple drones in the same collaborative airspace; Based on the cross-chain verification protocol, the validity of the SBT identity credential of each drone is verified to obtain a validity verification result, which includes valid SBT identity credentials and invalid SBT identity credentials. Based on verified and valid SBT identity credentials, consensus is reached among the multiple drones to construct a temporary task group; The formation information and member list of the temporary task group are recorded in the blockchain network; The registration method for the cross-chain SBT identity credential includes: Based on the three-phase encryption algorithm, an identity code for the drone is assigned, and the identity code for the drone is uploaded to the first blockchain to which the drone belongs; On the first blockchain to which the drone belongs, a digital identity credential for the drone is generated based on the drone's physical identity information, compliance credentials, and identity code. The target node of the first blockchain signs and endorses the initial attributes of the drone, generating a verifiable attribute declaration; Send the digital identity credential and the attribute declaration to the second blockchain; The second blockchain verifies the signature of the first blockchain, and after successful verification, generates a cross-chain SBT identity credential for the drone, wherein the cross-chain SBT identity credential includes the drone's identity digest, the verifiable attribute declaration, and an initialized dynamic reputation value.

[0041] In the above implementation, each UAV, within the cooperative airspace, announces its presence and exchanges its cross-chain SBT identity credentials by periodically broadcasting or responding to specific beacons. Upon receiving a credential from a neighboring node, any node initiates a cross-chain verification protocol. The core of this protocol is verifying whether the credential was legally issued by a trusted second blockchain and has not been revoked. This is typically accomplished by checking the credential's digital signature, querying its status on the second blockchain (its validity), and verifying the attribute declaration signature it contains, endorsed by the first blockchain. After verification, the node receives a list of local validity verification results, distinguishing trusted and untrusted nodes. Subsequently, all verified nodes form a candidate membership set.

[0042] In this application, the three-phase encryption algorithm is based on timestamps and ternary notation for encryption; the identity code is a static identity code generated by the three-phase encryption algorithm and burned into the drone chip, and the static identity code is unique and recorded on the first blockchain.

[0043] Specifically, during the factory deployment or initial registration phase of the drone, a unique static identification code is generated for each drone based on a three-phase encryption algorithm. When executed, the three-phase encryption algorithm obtains the current timestamp and uses this timestamp along with the drone's physical identification information (such as hardware serial number, manufacturing batch number, etc.) as encryption input. It then performs encryption operations according to ternary encoding rules to generate a unique static identification code. The generated static identification code is then burned into the drone's chip.

[0044] The three-phase encryption algorithm is an original encryption algorithm based on timestamps and ternary encoding. By combining timestamp information with ternary encoding rules, it generates a highly secure and unique encryption result. The static identity code is a fixed identity password generated by the three-phase encryption algorithm and written (burned) into the drone's chip. Once generated and burned, this identity code cannot be changed, possesses uniqueness, and is simultaneously recorded (on-chain) in the first blockchain to which the drone belongs, serving as an immutable physical identity identifier for the drone within the blockchain network.

[0045] In this embodiment of the application, the blockchain network includes a main chain and a secondary chain; The main chain consists of a data center and a command center, used to verify and store the static identity code and dynamic mission password of the drone; The secondary chain consists of an intermediary machine and a command center, and is generated according to the collaborative task, used to calculate and verify the dynamic task password; After the collaborative task is completed, all information of the secondary chain is uploaded to the main chain, and the secondary chain is deregistered. The individual nodes in the blockchain network consist of a command center, an intermediary machine, and a function machine. All individual nodes belong to the main chain. When a secondary chain is generated, the individual nodes join the corresponding secondary chain according to the scheduling information.

[0046] In the above implementation, the main chain consists of a data center and a command center, serving as the permanent core layer of the blockchain network. It is responsible for verifying and long-term storing the static identity codes and dynamic task passwords of all drones. The static identity codes of all drones are recorded on the main chain during the registration phase, serving as a globally trusted identity benchmark. The secondary chain consists of intermediary machines and the command center, dynamically generated according to specific collaborative tasks. When a collaborative task is triggered, the command center and the intermediary machines participating in the task jointly construct a secondary chain. This secondary chain is responsible for calculating and verifying the dynamic task password associated with the task during task execution, providing support for communication encryption and identity verification during the task. After the collaborative task is completed, all information in the secondary chain is uploaded to the main chain for permanent storage and archiving. Subsequently, the secondary chain is deregistered and no longer retained. Individual nodes in the blockchain network consist of the command center, intermediary machines, and functional machines. All individual nodes belong to the main chain by default. When a collaborative task generates a secondary chain, the corresponding individual node joins the corresponding secondary chain according to the received scheduling information, participating in the task password calculation and verification work on that secondary chain. After the task is completed, these nodes exit the secondary chain but retain their node status on the main chain.

[0047] In an alternative implementation, a cross-cluster authentication step is also included: When a cluster of drones or a single drone from outside the region enters the airspace of the current collaborative task, the command center on the main chain verifies the identity of the cluster of drones or the single drone from outside the region based on the identity information on the chain. After identity verification, depending on the command level and mission type, it is decided whether to add the drone cluster or individual drones outside the area into the command system of the temporary mission group. If you choose to join, the drone cluster or individual node corresponding to a single drone outside the area will be added to the secondary chain corresponding to the current collaborative task.

[0048] In the above embodiments, during the execution of collaborative tasks, it is possible for a cluster of drones or a single drone from outside the designated area to enter the current collaborative task airspace. This situation typically occurs when other command nodes are destroyed and their drones need to be transferred to a new command system, when long-distance or covert reinforcements from other command nodes arrive in the current task airspace, or when temporarily deployed drones need to join the current collaborative task.

[0049] When a drone swarm or a single drone from outside the designated area enters the airspace for the current collaborative task, the command center on the main chain first verifies the identity of the drone swarm or single drone based on on-chain identity information. The command center reads the static identity code record of the external drone and its associated cross-chain digital identity credential from the main chain, compares and verifies it with the identity information broadcast by the external drone, and confirms whether the external drone is a trusted entity that has been legally registered in the blockchain network.

[0050] After successful authentication, the command center, based on the command level and mission type of the current collaborative task, comprehensively determines whether to add the drone swarm or individual drone from outside the area to the command structure of the current temporary task group. The command center assesses whether the current mission requires additional troop support, whether the functionality of the external drone matches the current mission requirements, and whether the addition of the external drone would affect the security of the current command link. Based on the above assessment results, the command center makes a decision on whether to accept the drone.

[0051] If the command center chooses to add a drone swarm or individual drone from outside the area to the current command system, the individual node corresponding to that external drone swarm or individual drone will be added to the secondary chain corresponding to the current collaborative task. After being added to the secondary chain, the external drone can participate in the dynamic task password calculation and verification on the current secondary chain, receive task instructions distributed by the decision node, and be incorporated into the corresponding communication group according to the grouping rules of the current temporary task group, thereby realizing cross-swarm collaborative operations. Due to the characteristics of the three-phase encryption algorithm, swarms released by different units can automatically share identity and task data. The intermediary machine can directly schedule function machines in the surrounding swarms according to distance and functional requirements, without needing to distinguish the original unit to which the function machine belongs. At the same time, task information and function machine status will be reported to all relevant command centers simultaneously, ensuring that each command level can obtain complete situational information.

[0052] In one alternative implementation, constructing a temporary task group further includes a feature phone autonomously joining determination step: After receiving the collaborative task information, each feature phone obtains its own static identity code, function type, and distance information from the task target; Each feature phone independently determines whether to join the temporary task group based on its own static identity code, function type, and distance information; for feature phones that determine whether to join, their static identity code and dynamic task password are recorded on the blockchain network.

[0053] In the above implementation, each feature phone, based on its own static identity code, function type, and distance information, comprehensively evaluates its suitability for participating in the collaborative task according to a preset autonomous judgment logic. The judgment logic includes at least: whether its static identity code is valid in the blockchain network and has not been marked as abnormal; whether its function type belongs to the function category required by the collaborative task; and whether its distance from the task target is within the set effective response range. When all the above conditions are met, the feature phone autonomously decides to join the temporary task group.

[0054] For each feature machine selected for inclusion, its static identity code and dynamic task password are recorded on the blockchain network. Specifically, the feature machine associates its static identity code with the dynamic task password corresponding to the current collaborative task and submits the association record to the secondary chain corresponding to the current collaborative task. After the on-chain record is completed, the feature machine officially becomes a member of the temporary task group and can communicate with the intermediary machines in the group according to the communication rules agreed upon by the dynamic task password, receive task instructions, and execute corresponding collaborative operations. Through the feature machine autonomous inclusion judgment mechanism, it is unnecessary for the command center to dispatch each feature machine one by one. Instead, each feature machine can autonomously decide whether to participate in the collaborative task based on local information, which improves the task response speed and organizational flexibility of large-scale drone swarms in complex environments.

[0055] S2, within the temporary task group, at least one decision node is identified from multiple drones based on a preset multi-dimensional dynamic scoring model; In this embodiment of the application, the step of identifying the decision node from multiple drones based on a preset multidimensional dynamic scoring model includes: Obtain real-time status information of each UAV within the temporary task group, including computing resources, communication link quality, remaining energy, sensor payload type, topology stability, and dynamic reputation value; Each drone is given a first score based on its communication link quality, location, and topology stability. A second score for each drone is determined based on the degree of matching between the phase of the collaborative task and the sensor payload type of each drone, as well as the computing resources. A third score is determined for each drone based on its remaining energy, real-time power consumption, and predicted remaining flight time. A fourth score is determined for each drone based on its dynamic reputation value; Based on the stage and network status of the collaborative task, the weight information of multiple evaluation dimensions in the multidimensional dynamic scoring model is determined. Based on the weight information and the first, second, third, and fourth scores of each of the drones, at least one decision node is determined.

[0056] By comprehensively considering multiple key dimensions such as the node's communication hub performance (communication link quality, location, topology stability), task execution adaptability (matching sensor payload, computing resources, and task stage), continuous service capability (remaining energy and predicted endurance), and long-term behavioral reliability (dynamic reputation value), and dynamically adjusting the weights of each dimension based on the task stage and network conditions, the elected decision-making nodes are not only highly capable but also well-matched to the needs of collaborative tasks. This improves the overall decision-making quality, response efficiency, and adaptability of temporary task groups when facing different task stages, different threat types, and different network conditions.

[0057] S3, within the temporary task group, based on a preset password generation algorithm and collaborative tasks, a dynamic task password associated with the collaborative tasks is generated and distributed to each UAV within the task group. The dynamic task password specifies the temporary identification signal, encryption algorithm, and communication protocol used by the UAV in the temporary task group. In this embodiment of the application, based on a preset password generation algorithm and a collaborative task, a dynamic task password associated with the collaborative task is generated and distributed to each drone in the task group, including: Based on the task phase of the collaborative task, the decision node determines the target codebook type to be activated from a set of preset codebooks. Based on the target password type, the decision node generates dynamic task passwords corresponding to the temporary task group in real time using a three-phase encryption algorithm. The decision node distributes the generated dynamic task password to each drone in the temporary task group; The decision node communicates with each UAV according to the fixed-point communication time, decoding method and password change timestamp agreed upon by the dynamic task password.

[0058] In this embodiment of the application, the dynamic task password refers to the encryption password temporarily generated based on the three-phase encryption algorithm and associated with the collaborative task after the command center distributes the collaborative task. The password is used to specify the temporary identification signal, encryption algorithm and communication protocol used by the UAVs in the temporary task group. It has the characteristic of "cancellation after use", that is, it is cancelled after the collaborative task is completed.

[0059] A codebook refers to a set of encryption parameters pre-configured in a UAV identification system. Each UAV's identification system contains multiple codebooks, each corresponding to different encryption rules and communication parameters. The target codebook type refers to the specific codebook selected from multiple preset codebooks based on the task phase of the collaborative mission. The fixed-point communication time refers to the specific point in time, agreed upon by the dynamic task cryptography, for communication between the decision node and each UAV.

[0060] Multiple elected decision nodes, acting as trusted cryptographic distribution centers, begin their work. Based on the context of the current collaborative task and potential threat assessment, these nodes intelligently select the most suitable target cryptographic type from a pre-defined cryptographic type library. Once the type is selected, the decision nodes, using a three-phase encryption algorithm, instantly generate the dynamic task cryptography corresponding to the temporary task group. During the generation process, the three-phase encryption algorithm incorporates current timestamp information and ternary encoding rules for encryption operations, ensuring the generated dynamic task cryptography possesses both timeliness and uniqueness.

[0061] After generation, the decision node needs to securely distribute it to every member of the task group, ensuring that all drones in the group possess a unified password associated with the current collaborative task. Once the dynamic task password is distributed, the decision node and each drone communicate according to the fixed-point communication time, decoding method, and password change timestamp agreed upon in the dynamic task password. Specifically, each communicating party sends and receives data at the specific time points agreed upon in the dynamic task password, decrypts the received data using the agreed-upon decoding method, and changes the password when the agreed-upon change timestamp arrives.

[0062] As an optional implementation method in this application, it further includes: Based on the current parameters of the dynamic task password and the preset grouping algorithm, the UAVs in the temporary task group are divided into multiple hierarchical communication groups. Each group includes at least one intermediary machine and one function machine. The intermediary machine represents a node responsible for communicating with the upper layer within the group, and the function machine represents a node that communicates with the intermediary machine within the group. The role of the intermediary machine changes within its group according to the received encryption instructions. Within each group, an online intermediary machine communicates with the decision node. If the online intermediary machine fails, a new intermediary machine is replaced in the group where the failed intermediary machine is located according to a predetermined replacement rule. The functional machines in each group communicate with the intermediary machines in the group.

[0063] When the intermediary machine communicates with the functional machines in this group, it obtains the authentication feedback of all functional machines in this group. If the authentication feedback of all functional machines is not obtained, the authentication of the intermediary machine fails. When intermediary machines in different communication groups communicate with each other, they exchange and verify the grouping credentials issued by the decision node. If the grouping credentials fail to be verified, the communication authentication fails.

[0064] In this embodiment, the grouping credential refers to credential information issued by the decision node for authentication between different communication groups. The predetermined replacement rule refers to the specification for selecting a new intermediary machine within a group according to pre-set rules when an online intermediary machine within that group fails.

[0065] Specifically, after the dynamic task cipher is generated and distributed to each drone within the temporary task group, the drones within the temporary task group are divided into multiple hierarchical communication groups based on the current parameters of the dynamic task cipher and a preset grouping algorithm. Each group includes at least one intermediary machine and one function machine. The intermediary machine is responsible for communication between the group and the upper layer (i.e., the decision-making node or command system), while the function machine is responsible for communication with the intermediary machine within the group. The role of the intermediary machine is not fixed but dynamically changes within its group based on the received encryption instructions. That is, which drone in the group assumes the role of the intermediary machine changes randomly depending on the encryption instructions, thereby enhancing the group's anti-attack capability and communication security.

[0066] In the communication structure of each formation, an online intermediary machine communicates directly with the decision node, responsible for receiving task instructions and reporting status information within the formation. If the online intermediary machine fails due to malfunction, being shot down, or communication interruption, a new intermediary machine is replaced within the formation according to a predetermined replacement rule. The new intermediary machine takes over the communication responsibilities with the decision node, ensuring uninterrupted communication within the formation. Functional machines within each formation only communicate with the intermediary machine within their own formation and do not communicate directly with the decision node or UAVs in other formations.

[0067] It should be noted that during intra-group communication, when the intermediary machine communicates with the functional machines within the same group, it needs to obtain authentication feedback from all functional machines in the group. That is, the intermediary machine sends authentication requests to all functional machines in the group, and only when all functional machines return valid authentication feedback is the intermediary machine's authentication considered successful. If authentication feedback is not received from all functional machines, for example, if a functional machine does not respond or returns invalid authentication information, the intermediary machine's authentication fails. The system will handle this exception to prevent spoofed or compromised nodes from infiltrating intra-group communication.

[0068] During communication between different communication groups, when intermediary machines in different communication groups communicate with each other, they need to exchange and verify grouping credentials issued by the decision node. Each group, after its formation, is issued a unique grouping credential by the decision node, which contains the group identifier and the decision node's signature information. When intermediary machines in two groups need to communicate across groups, they first exchange their respective grouping credentials and verify the decision node's signature in the other's credential. If the grouping credential verification passes, the cross-group communication authentication is successful, and both parties can exchange data; if the grouping credential verification fails, the communication authentication fails, and the system rejects the cross-group communication request to prevent unauthorized groups or spoofed groups from accessing the communication network.

[0069] In one alternative implementation, the method further includes: In response to the number of drones in the temporary task group reaching a first threshold, multiple intermediary drones are further grouped to form a higher-level intermediary cluster, constituting a swarm group. In the intermediary cluster, a superior intermediary machine is dynamically designated according to the encryption instructions, and the role of the superior intermediary machine changes randomly according to the different encryption instructions. In response to the spatial distance between two communication groups being less than a set threshold or their flight paths being similar, the two communication groups are automatically triggered to form an intermediate layer group to coordinate their communication and actions.

[0070] Specifically, during the operation of temporary task groups, as the scale of collaborative tasks expands or the number of participating drones increases, it is necessary to further enhance the grouping hierarchy to ensure communication efficiency and command order. When the number of drones responding to a temporary task group reaches a first threshold, multiple intermediary drones are further grouped to form a higher-level intermediary cluster, thus constituting a swarm group. The swarm group is a higher-level hierarchical organizational structure formed on the basis of the original communication grouping, in which the intermediary cluster acts as the intermediate command layer, responsible for coordinating and managing the multiple communication groups under its jurisdiction.

[0071] In the aforementioned intermediary cluster, a superior intermediary machine is dynamically assigned based on encrypted instructions. This superior intermediary machine is responsible for communicating with decision-making nodes or the command system, and for information aggregation and instruction forwarding within the cluster. The role of the superior intermediary machine is not fixed but changes randomly based on different encrypted instructions. That is, each time a new encrypted instruction is received, the specific UAV within the cluster assuming the role of the superior intermediary machine may change. This dynamic change mechanism effectively prevents adversaries from disrupting the entire cluster's command link by locking onto specific communication nodes, enhancing the swarm's resilience and survivability.

[0072] Furthermore, in the actual operation of temporary task groups, when the spatial distance between two communication groups is detected to be less than a set threshold or their flight paths are similar, the two communication groups are automatically triggered to form an intermediate layer group to coordinate their communication and actions. The establishment of the intermediate layer group allows spatially adjacent groups or groups with similar flight paths to directly coordinate and share information without going through the top-level decision-making node, reducing communication latency and improving the speed of collaborative response. For example, when the flight paths of two groups are about to intersect or the mission areas of the two groups overlap, the intermediate layer group is automatically generated. The intermediary aircraft of the two groups communicate directly through the intermediate layer group to coordinate the flight paths and task allocation of the UAVs within their respective groups, avoiding conflicts and achieving more efficient collaborative operations.

[0073] S4. In response to a collaborative perception request for an abnormal target sent by any UAV in the temporary task group, based on dynamic task cryptography, coordinate multiple UAVs in the task group to perform multi-source collaborative perception and cross-verification of the abnormal target, and generate a threat assessment result. In this embodiment of the application, before responding to a cooperative perception request for an abnormal target sent by any UAV within the temporary task group, a multi-source cooperative target acquisition step is further included: The system acquires radar information from the command system as a third-party source. When an incorrect identification signal is detected in the operational airspace, the system publishes the location information of the incorrect identification signal to the grouping intermediary and command system, and marks the corresponding object as abnormal. Obtain the airborne radar information of each UAV in the temporary task group. When the airborne radar detects additional or abnormal spatial locations, mark the corresponding objects as abnormal. Obtain the recognition results of the image recognition system of each UAV in the temporary task group. When the image recognition system detects a target outside the group, mark the corresponding object as abnormal. The communication signals in the airspace where the temporary task group is located are obtained. When an unconventional communication signal is detected, the abnormal signal source is identified and locked, and the corresponding object is marked as abnormal. Based on the anomaly marker, the collaborative perception request for the anomaly target is generated.

[0074] In this embodiment of the application, S4 includes: Obtain a collaborative perception request sent by any UAV, wherein the collaborative perception request represents a request for dynamic task cryptographic encryption signature of the communication group to which the UAV belongs, and the collaborative perception request includes preliminary characteristic information of abnormal targets; Based on the collaborative sensing request and the real-time location, sensor payload type and remaining energy of each UAV in the task group, multiple UAVs participating in collaborative sensing are identified as task nodes. Based on the dynamic task password corresponding to each task node, encrypted concrete perception instructions are distributed to each task node so that each task node can perform a perception task and obtain a perception evidence package. Obtain the perception evidence packet returned by each of the task nodes, which is dynamically password-signed by itself. Spatiotemporal alignment and cross-validation are performed on the perceptual evidence of each task node to obtain the cross-validation results; Based on the results of cross-validation, the cross-chain digital identity credentials of the abnormal target queried from the blockchain network, and the preset threat assessment model, the threat assessment result is determined and a summary of the threat assessment result is recorded on the blockchain network. The threat assessment result includes the threat level and confidence level.

[0075] In this embodiment, the threat assessment model is an intelligent decision-making algorithm module based on rule-based reasoning and multi-dimensional evidence fusion. It standardizes, quantifies, weights, and logically judges three types of heterogeneous evidence: cross-validation results from multiple sensors in physical space, the status of blockchain digital identity credentials from cyberspace, and behavioral pattern characteristics obtained through real-time trajectory analysis of the target. Specifically, the model first converts each piece of evidence into numerical scores: for example, it assigns preset base scores to different states such as valid, invalid, and revoked identity credentials; it weights the consistency ratio of verification results from multiple drone nodes, combined with the reputation value of each node, to obtain a collaborative verification credibility score; simultaneously, it analyzes whether the target's flight path intrudes into no-fly zones, performs close-in or evasive maneuvers, matches it against a preset threat behavior database, and accumulates abnormal behavior scores. Subsequently, the model dynamically assigns weights to each score according to the current mission stage (such as patrol or engagement), and calculates a comprehensive threat value through weighted summation. Ultimately, the overall threat value is compared with a predefined threshold range and mapped to discrete threat levels such as "harmless, suspicious, malicious, and hostile," while a percentage confidence level is calculated by combining the sufficiency and consistency of the evidence.

[0076] S5, the threat assessment results are sent to each of the decision nodes, so that each of the decision nodes generates a consensus-signed security operation instruction based on the consensus mechanism; In this embodiment of the application, each of the decision nodes generates a consensus-signed secure operation instruction based on a consensus mechanism, including: For any decision node, after obtaining the threat assessment result, the decision node will be used as a proposal node and will generate candidate security operation instructions based on a preset hierarchical response strategy library. The proposal node broadcasts the candidate security operation instructions to all decision nodes in the temporary task group based on the high-level dynamic task password, whereby the high-level dynamic task password is a dynamic task password agreed upon between the decision nodes. For each decision node that obtains candidate security operation instructions, the obtained candidate security operation instructions are reviewed and voted on to obtain the voting results; The proposal node obtains the voting results of all decision nodes. If the number of "agree" votes in the voting results exceeds a preset threshold, it is determined that a consensus has been reached, and the candidate security operation instruction is determined as the final security operation instruction. Each decision node that votes in favor performs multi-signature on the final secure operation instruction based on its own private key, generating a consensus-signed secure operation instruction.

[0077] The system takes effect after being reviewed and voted on by multiple independent decision-making nodes and receiving more than a preset threshold of approval. Once the instruction takes effect, all decision-making nodes that voted in favor use their respective private keys to multi-sign it, making the final secure operation instruction unforgeable. At the same time, the consensus process is combined with blockchain notarization, and the voting results, final instructions, and multi-signatures are all recorded on the blockchain, making the entire decision-making chain completely transparent, auditable, and tamper-proof.

[0078] S6, based on the security operation command and the dynamic task password, determine the target drone and schedule the target drone to perform corresponding cooperative countermeasure operations; and, Key event data generated during this collaborative task will be recorded on the blockchain network to trigger the blockchain to update the dynamic reputation value in the target drone's cross-chain digital identity credential based on the key event data.

[0079] In this embodiment of the application, the step of determining the target drone based on the security operation command and the dynamic task password, and scheduling the target drone to perform corresponding cooperative countermeasure operations, includes: Based on a preset signature verification method, the validity of the multi-digital signature on the secure operation instruction signed by consensus is verified. After successful verification, the security operation instructions are parsed to obtain the countermeasure strategy, expected effect and constraints, and the countermeasure strategy is decomposed into multiple sub-tasks. Based on the status information of each UAV in the temporary task group and the preset distributed scheduling optimization model, at least one optimal target UAV is matched for each subtask. The scheduling optimization model takes minimizing the overall task completion time, maximizing the success probability of execution, and balancing the UAV load as the objective function, and comprehensively considers the status information of each candidate UAV, the distance between the candidate UAV and the subtask location, the matching degree between the sensor and the payload and the subtask, and the dynamic reputation value for optimization calculation. A corresponding encrypted executable task package is generated for each target drone. The encrypted executable task package is encrypted based on the dynamic task password corresponding to the target drone and encapsulates the details of the assigned subtask, the collaborative time window, the action path planning, and the authorization credential fragment extracted from the consensus-signed secure operation instruction. The encrypted executable task package is sent to the corresponding target drone through the intermediary machine of the group to which each target drone belongs; For any of the target drones, after acquiring and decrypting the encrypted executable task package, the target drone verifies the validity of the authorization credential fragment encapsulated in the decrypted executable task package, and executes the sub-task within a set time window after the verification is successful. For any of the target drones, during the execution process, the target drone will transmit its execution status back after being encrypted and signed by the target drone's dynamic task password; Based on the returned execution status information, the execution progress of all subtasks is monitored, and the execution process is dynamically coordinated and conflict resolved according to preset rules. After the coordinated countermeasures operation is completed, the execution logs of each target drone are obtained, and the hash value of the execution logs, the final task completion status, and the effect evaluation are recorded as key event data on the blockchain network to trigger the update of the dynamic reputation value of the relevant drones.

[0080] In this embodiment, any node designated as a scheduling execution role (which may be one of the decision nodes or a dedicated scheduling node) first verifies the validity of the multi-signature on the instruction upon receiving it. This serves as the "legitimacy switch" for all subsequent actions. After successful verification, the node parses the instruction and intelligently decomposes it into a series of atomic subtasks that can be assigned to a single UAV for execution.

[0081] Subsequently, the scheduling node obtains the real-time status of all UAVs within the task group and invokes a pre-defined distributed scheduling optimization model. This model, using mathematical programming, comprehensively considers each UAV's position (determining arrival time), sensors / payloads (determining whether a specific subtask can be executed), remaining energy (determining continuous operation), and dynamic reputation value (determining execution reliability). It optimizes the solution under multiple objectives, including "shortest total time, highest success rate, and balanced load across all UAVs," selecting the optimal target UAV for each subtask. Next comes the secure distribution and activation of the task. For each selected target UAV, the scheduling node generates an encrypted executable task package. This executable task package is encrypted using a target UAV-specific dynamic task password and contains extremely detailed information, including subtask details, a precise coordination time window, a suggested flight path, and crucial authorization credential fragments. The task package is securely delivered through an established hierarchical communication network (via the intermediary machines in each UAV's group). After receiving the package, the target UAV completes two crucial steps locally: decryption and authorization credential verification, before autonomously executing within the specified time window. During execution, each machine needs to encrypt and sign key execution status and then transmit it back in real time, so that the scheduling node or monitoring node can monitor the progress globally.

[0082] This method establishes verifiable and trustworthy digital identities for drones from different management domains using blockchain-based cross-chain digital identity credentials. This enables the construction of temporary task groups in open airspace without the need for central authority intervention, fundamentally solving the cross-management domain mutual trust problem. Dynamically generated and task-bound dynamic task passwords provide an independent, temporary, and secure communication environment for each collaborative task. Utilizing distributed sensing resources within the temporary task group, and through multi-source information cross-verification and swarm intelligence assessment models, the accuracy of threat identification and assessment in complex air situations is improved. Finally, blockchain technology is used to immutably record key events throughout the entire process, forming a traceable airspace security ledger.

[0083] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0084] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A drone collaborative method based on blockchain and three-phase encryption algorithm, characterized in that, include: A temporary task group is constructed based on the cross-chain digital identity credentials of multiple drones. The multiple drones are drones that enter the same collaborative airspace. The cross-chain digital identity credentials are generated and registered in the blockchain network. The cross-chain digital identity credentials include the verifiable attributes and dynamic reputation value of the drones. The verifiable attributes represent the physical identity, hardware capabilities and mission qualifications of the drones. The dynamic reputation value represents the behavior and contribution of the drones in historical collaborative tasks. Within the temporary task group, at least one decision node is identified from multiple drones based on a preset multidimensional dynamic scoring model. Within the temporary task group, based on a preset password generation algorithm and collaborative tasks, a dynamic task password associated with the collaborative tasks is generated and distributed to each UAV in the task group. The dynamic task password specifies the temporary identification signal, encryption algorithm, and communication protocol used by the UAV in the temporary task group. In response to a collaborative perception request for an abnormal target sent by any UAV within the temporary task group, based on dynamic task cryptography, multiple UAVs within the temporary task group are coordinated to perform multi-source collaborative perception and cross-verification of the abnormal target, generating a threat assessment result. The threat assessment results are sent to each of the decision nodes, so that each of the decision nodes generates a consensus-signed security operation instruction based on the consensus mechanism. Based on the security operation instructions and the dynamic task password, the target drone is identified, and the target drone is scheduled to perform corresponding coordinated countermeasures. as well as, Key event data generated during this collaborative task will be recorded on the blockchain network to trigger the blockchain to update the dynamic reputation value in the target drone's cross-chain digital identity credential based on the key event data.

2. The UAV collaborative method based on blockchain and three-phase encryption algorithm according to claim 1, characterized in that, The temporary task group, constructed based on cross-chain digital identity credentials from multiple drones, includes: Obtain cross-chain SBT identity credentials broadcast separately by multiple drones in the same collaborative airspace; Based on the cross-chain verification protocol, the validity of the SBT identity credential of each drone is verified to obtain a validity verification result, which includes valid SBT identity credentials and invalid SBT identity credentials. Based on verified and valid SBT identity credentials, consensus is reached among the multiple drones to construct a temporary task group; The formation information and member list of the temporary task group are recorded in the blockchain network; The registration method for the cross-chain SBT identity credential includes: Based on the three-phase encryption algorithm, an identity code for the drone is assigned, and the identity code for the drone is uploaded to the first blockchain to which the drone belongs; On the first blockchain to which the drone belongs, a digital identity credential for the drone is generated based on the drone's physical identity information, compliance credentials, and identity code. The target node of the first blockchain signs and endorses the initial attributes of the drone, generating a verifiable attribute declaration; Send the digital identity credential and the attribute declaration to the second blockchain; The second blockchain verifies the signature of the first blockchain, and after successful verification, generates a cross-chain SBT identity credential for the drone, wherein the cross-chain SBT identity credential includes the drone's identity digest, the verifiable attribute declaration, and an initialized dynamic reputation value.

3. The UAV collaborative method based on blockchain and three-phase encryption algorithm according to claim 2, characterized in that, The three-phase encryption algorithm is based on timestamps and ternary notation for encryption; the identity code is a static identity code generated by the three-phase encryption algorithm and burned into the drone chip, and the static identity code is unique and recorded on the first blockchain.

4. The UAV collaborative method based on blockchain and three-phase encryption algorithm according to claim 2, characterized in that, The blockchain network includes a main chain and secondary chains; The main chain consists of a data center and a command center, used to verify and store the static identity code and dynamic mission password of the drone; The secondary chain consists of an intermediary machine and a command center, and is generated according to the collaborative task, used to calculate and verify the dynamic task password; After the collaborative task is completed, all information of the secondary chain is uploaded to the main chain, and the secondary chain is deregistered. The individual nodes in the blockchain network consist of a command center, an intermediary machine, and a function machine. All individual nodes belong to the main chain. When a secondary chain is generated, the individual nodes join the corresponding secondary chain according to the scheduling information.

5. The drone collaborative method based on blockchain and three-phase encryption algorithm according to claim 1, characterized in that, The process of generating and distributing dynamic task passwords associated with the collaborative task to each UAV in the task group, based on a preset password generation algorithm and collaborative task, includes: Based on the task phase of the collaborative task, the decision node determines the target codebook type to be activated from a set of preset codebooks. Based on the target password type, the decision node generates dynamic task passwords corresponding to the temporary task group in real time using a three-phase encryption algorithm. The decision node distributes the generated dynamic task password to each drone in the temporary task group; The decision node communicates with each UAV according to the fixed-point communication time, decoding method and password change timestamp agreed upon by the dynamic task password; After the collaborative task is completed, all intermediary machines and feature machines in the same area will deregister the dynamic task password.

6. The UAV collaborative method based on blockchain and three-phase encryption algorithm according to claim 5, characterized in that, Also includes: Based on the current parameters of the dynamic task password and the preset grouping algorithm, the UAVs in the temporary task group are divided into multiple hierarchical communication groups. Each group includes at least one intermediary machine and one function machine. The intermediary machine represents a node responsible for communicating with the upper layer within the group, and the function machine represents a node that communicates with the intermediary machine within the group. The role of the intermediary machine changes within its group according to the received encryption instructions. Within each group, an online intermediary machine communicates with the decision node. If the online intermediary machine fails, a new intermediary machine is replaced in the group where the failed intermediary machine is located according to a predetermined replacement rule. The functional machines in each group communicate with the intermediary machines in the group. When the intermediary machine communicates with the functional machines in this group, it obtains the authentication feedback of all functional machines in this group. If the authentication feedback of all functional machines is not obtained, the authentication of the intermediary machine fails. When intermediary machines in different communication groups communicate with each other, they exchange and verify the grouping credentials issued by the decision node. If the grouping credentials fail to be verified, the communication authentication fails.

7. The UAV collaborative method based on blockchain and three-phase encryption algorithm according to claim 6, characterized in that, Also includes: In response to the number of drones in the temporary task group reaching a first threshold, multiple intermediary drones are further grouped to form a higher-level intermediary cluster, constituting a swarm group. In the intermediary cluster, a superior intermediary machine is dynamically designated according to the encryption instructions, and the role of the superior intermediary machine changes randomly according to the different encryption instructions. In response to the spatial distance between two communication groups being less than a set threshold or their flight paths being similar, the two communication groups are automatically triggered to form an intermediate layer group to coordinate their communication and actions.

8. A drone collaborative method based on blockchain and three-phase encryption algorithm according to claim 6, characterized in that, Prior to responding to a cooperative perception request for an abnormal target sent by any UAV within the temporary task group, a multi-source cooperative target acquisition step is also included: The system acquires radar information from the command system as a third-party source. When an incorrect identification signal is detected in the operational airspace, the system publishes the location information of the incorrect identification signal to the grouping intermediary and command system, and marks the corresponding object as abnormal. Obtain the airborne radar information of each UAV in the temporary task group. When the airborne radar detects additional or abnormal spatial locations, mark the corresponding objects as abnormal. Obtain the recognition results of the image recognition system of each UAV in the temporary task group. When the image recognition system detects a target outside the group, mark the corresponding object as abnormal. The communication signals in the airspace where the temporary task group is located are obtained. When an unconventional communication signal is detected, the abnormal signal source is identified and locked, and the corresponding object is marked as abnormal. Based on the anomaly marker, the collaborative perception request for the anomaly target is generated.

9. A drone collaborative method based on blockchain and three-phase encryption algorithm according to claim 4, characterized in that, It also includes cross-cluster authentication steps: When a cluster of drones or a single drone from outside the region enters the airspace of the current collaborative task, the command center on the main chain verifies the identity of the cluster of drones or the single drone from outside the region based on the identity information on the chain. After identity verification, depending on the command level and mission type, it is decided whether to add the drone cluster or individual drones outside the area into the command system of the temporary mission group. If you choose to join, the drone cluster or individual node corresponding to a single drone outside the area will be added to the secondary chain corresponding to the current collaborative task.

10. A drone collaborative method based on blockchain and three-phase encryption algorithm according to claim 1, characterized in that, The construction of the temporary task group also includes a step for determining whether the feature phone can automatically join: After receiving the collaborative task information, each feature phone obtains its own static identity code, function type, and distance information from the task target; Each feature phone independently determines whether to join the temporary task group based on its own static identity code, function type, and distance information; for feature phones that determine whether to join, their static identity code and dynamic task password are recorded on the blockchain network.

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