A method and system for identifying malicious route disruption attacks in a drone swarm networking

Abstract

The application discloses a kind of unmanned aerial vehicle swarm networking in malicious routing interruption attack identification method and system, based on blockchain technology realizes unmanned aerial vehicle cluster distributed network information collection, free from the restriction of centralized detection, guarantee unmanned aerial vehicle to obtain the reliability and accuracy of node information, improve the stability and robustness of network;Periodically call smart contract, detect whether unmanned aerial vehicle node exists attack behavior, judge the security of each unmanned aerial vehicle node, guarantee the safety communication between nodes;The scheme realizes self-command and control, reduces human intervention, improves the efficiency of task execution, simultaneously makes network more adaptable, improves the overall performance and security level of network;Through smart contract technology, network layer information intrusion can be effectively detected, and security protection is provided for network security;The above scheme has wide application prospect in the field of network security monitoring, attack defense and the like, and helps to build safer and more reliable network environment.

Description

Technical Field

[0001] This invention relates to the fields of drone swarm technology and blockchain technology, and in particular to a method and system for identifying malicious routing interruption attacks in drone swarm networking. Background Technology

[0002] In recent years, with the rapid development of drone technology, drone swarms have been widely used in emergency search and rescue, traffic control, and military operations. However, due to the limited resources of drones themselves, it is difficult to deploy complex security modules. Furthermore, drone swarms are vulnerable to network attacks due to their dynamic topology, intermittent links, and unreliable transmission. Traditional drone swarms typically employ a centralized control method, with a central node controlling and coordinating all other nodes. When the central node is attacked or damaged, the entire swarm may lose its ability to coordinate. To achieve high scalability and robustness in drone swarm networks and realize a decentralized, secure, and reliable collaborative approach, a distributed drone swarm networking architecture needs to be constructed.

[0003] Blockchain technology offers new possibilities for solving security issues in drone systems. With its key characteristics of traceability, data immutability, and decentralization, blockchain can effectively improve the security and reliability of mission data. Combining distributed ledgers, asymmetric encryption, and smart contracts, blockchain boasts extremely high security performance. Applying blockchain technology to drone swarms allows the distributed ledger to record network layer information of the drone system, while smart contracts enable the verification and inspection of this information. This design not only ensures the integrity of network information but also allows for the tracking and tracing of changes in routing information, providing an effective means to prevent network layer intrusion.

[0004] Malicious routing disruption attacks refer to network attacks where malicious nodes receive data but fail to forward it, preventing the data from reaching its destination. Attackers manipulate network routing to interrupt normal data transmission, disrupting communication traffic and services, causing serious harm to the communication network. Therefore, identifying nodes causing malicious routing disruptions and protecting network routing security is crucial. Figure 1As shown, traditional route interruption detection employs a centralized approach. Each drone node maintains a list recording its received and transmitted data volumes. The central node calculates the node's total received and transmitted traffic based on this list. When the transmitted traffic is significantly lower than the received traffic, the node is identified as a malicious node experiencing a route interruption. However, because the list recording local transmitted and received traffic is maintained by the node itself, an attacker who controls the node can fill in false received and transmitted traffic information to interfere with the central node's judgment. If the attacker compromises the central node, the entire system becomes unable to detect malicious route interruption attacks. Therefore, traditional identification schemes based on list-based traffic information cannot accurately identify the occurrence of route interruptions. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for identifying malicious routing interruption attacks in drone swarm networks, which can effectively resist malicious routing interruption attacks in the network and protect the communication security of drone swarm networks.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A method for identifying malicious routing disruption attacks in drone swarm networking includes:

[0008] The blockchain network is integrated with the drone swarm network, in which each drone node is connected to the blockchain network and uploads its received traffic information to the blockchain.

[0009] In a drone swarm network, drone nodes take turns calling smart contracts in the blockchain network to identify malicious routing interruption attacks. The smart contract checks the block records in the blockchain network over a period of time, calculates the received and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies nodes that are maliciously interrupting traffic attacks.

[0010] A system for identifying malicious routing disruption attacks in a drone swarm network includes: a blockchain network and a drone swarm network; the blockchain network deploys smart contracts, and the drone swarm network contains multiple drone nodes; wherein:

[0011] The blockchain network is integrated with the drone swarm network. Each drone node in the drone swarm network is connected to the blockchain network and uploads its received traffic information to the blockchain network.

[0012] In a drone swarm network, drone nodes take turns calling smart contracts in the blockchain network to identify malicious routing interruption attacks. The smart contract checks the block records in the blockchain network over a period of time, calculates the received and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies nodes that are maliciously interrupting traffic attacks.

[0013] As can be seen from the technical solution provided by the present invention, the distributed network information collection of drone swarms based on blockchain technology constructs a decentralized network architecture, eliminating the limitations of centralized detection, ensuring the reliability and accuracy of node information acquired by drones, and improving the stability and robustness of the network. By periodically calling smart contracts, it detects whether drone nodes exhibit attack behavior, assesses the security of each network node, and ensures secure communication between nodes. This solution achieves autonomous task command and control, reduces human intervention, improves task execution efficiency, and makes the network more adaptable, thereby enhancing the overall performance and security level of the network. Through smart contract technology, it can effectively detect network layer information intrusion and provide security guarantees for network security. The above solution has broad application prospects in areas such as network security monitoring and attack defense, and helps to build a safer and more reliable network environment. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A schematic diagram illustrating traditional route disruption attack detection, provided as part of the background technology of this invention;

[0016] Figure 2 A flowchart illustrating a method for identifying malicious routing disruption attacks in a drone swarm network, provided as an embodiment of the present invention;

[0017] Figure 3 A schematic diagram illustrating blockchain-based traffic information collection provided in an embodiment of the present invention;

[0018] Figure 4 This is a schematic diagram illustrating the identification of routing interruption attacks based on smart contracts, provided as an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0020] First, the following explanations are provided for the terms that may be used in this article:

[0021] The terms “including,” “comprising,” “containing,” “having,” or other similar semantic descriptions should be interpreted as non-exclusive inclusion. For example, “including a technical feature element (such as raw material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, device, step, process, method, reaction conditions, processing conditions, parameter, algorithm, signal, data, product or article of manufacture, etc.)” should be interpreted as including not only the expressly listed technical feature element, but also other technical feature elements that are not expressly listed and are well-known in the art.

[0022] The term "composed of" excludes any technical features not expressly listed. When used in a claim, it closes the claim to exclude all technical features other than those expressly listed, except for associated conventional impurities. If the term appears only in a clause of a claim, it limits the claim to the elements expressly listed in that clause; elements recited in other clauses are not excluded from the overall claim.

[0023] The following provides a detailed description of a method and system for identifying malicious routing disruption attacks in drone swarm networking, as provided by this invention. Contents not described in detail in the embodiments of this invention are prior art known to those skilled in the art. Where specific conditions are not specified in the embodiments of this invention, they should be performed according to conventional conditions in the art or conditions recommended by the manufacturer.

[0024] Example 1

[0025] This invention provides a method for identifying malicious routing disruption attacks in drone swarm networks. For example... Figure 1 As shown, it mainly includes:

[0026] 1. Integrate the blockchain network with the drone swarm network. In the drone swarm network, each drone node is connected to the blockchain network and uploads its received traffic information to the blockchain.

[0027] In this embodiment of the invention, after each drone node receives a data packet sent by another drone node, it records the drone node ID that sent the data packet, its own ID, and the relevant data packet, and uploads them to the blockchain network as received traffic information.

[0028] 2. Drone nodes in the drone swarm network take turns calling smart contracts in the blockchain network to identify malicious routing interruption attacks.

[0029] In this embodiment of the invention, the smart contract includes an attack detection interface and a result query interface; wherein, the drone node identifies malicious routing interruption attacks by calling the attack detection interface of the smart contract; and the drone node queries the results of the malicious routing interruption attack identification by calling the result query interface of the smart contract.

[0030] In this embodiment of the invention, the malicious routing interruption attack identification process is as follows: The smart contract checks the block records in the blockchain network over a period of time, calculates the received traffic information and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies the malicious routing interruption attack node accordingly; specifically: if the received traffic of a drone node is not 0 and the sent traffic is 0, then the corresponding drone node is judged as a malicious routing interruption attack node; or, if the sent traffic of a drone node is less than a threshold, then the corresponding drone node is judged as a malicious routing interruption attack node.

[0031] The above-mentioned solution provided by the embodiments of the present invention can effectively resist malicious routing interruption attacks in the network and protect the communication security of drone swarm networking. Based on blockchain technology, it realizes distributed network information collection for drone swarms, constructs a decentralized network architecture, overcomes the limitations of centralized detection, ensures the reliability and accuracy of node information acquired by drones, and improves network stability and robustness. This invention proposes a blockchain-based network information intrusion identification technology and designs a malicious routing interruption attack identification scheme based on smart contracts. By periodically calling smart contracts, it detects whether drone nodes exhibit attack behavior, judges the security of each network node, and ensures secure communication between nodes. This scheme realizes autonomous task command and control, reduces human intervention, improves task execution efficiency, and makes the network more adaptable, improving the overall network performance and security level. Through smart contract technology, it can effectively detect network layer information intrusion and provide security guarantees for network security. This technology has broad application prospects in network security monitoring, attack defense, and other fields, and helps to build a safer and more reliable network environment.

[0032] To more clearly demonstrate the technical solution and its effects provided by the present invention, the method provided by the embodiments of the present invention will be described in detail below with reference to specific examples.

[0033] I. Introduction to the principle of the scheme.

[0034] Traditional drone swarm networks employ a centralized method for identifying malicious route disruptions, with a central node coordinating and making judgments. When the central node is attacked or damaged, the entire swarm loses its ability to coordinate and cannot identify malicious route disruptions. Furthermore, when the traffic information of other nodes is tampered with, traditional solutions also fail to accurately identify the occurrence of route disruptions.

[0035] Blockchain data is stored across distributed nodes in the network, rather than centrally on a single server. Each node has a complete copy of the data. This makes it very difficult for attackers to tamper with or compromise the data across the entire network. Even if one node is attacked, the entire network can still function normally. Blockchain uses cryptographic algorithms to protect the confidentiality and integrity of data, making it difficult for data to be stolen or tampered with during transmission and storage. Applying blockchain to drone swarm networks can help protect mission data security, promote innovation in mission execution methods, and enhance network security.

[0036] Therefore, this invention utilizes UAV networking technology with built-in blockchain to address the problem of identifying network layer information intrusion in UAV systems. It combines this with smart contract technology to construct a malicious routing interruption identification method in UAV swarm networking, transforming the centralized model into a decentralized distributed model. The blockchain can record various information from the UAV system and protect it for continuous monitoring in a database. Combined with smart contracts, an autonomous task command and control system can be built, enabling automatic verification, authorization, and execution of tasks, reducing human intervention and potential security risks. This improves task execution efficiency and promotes innovation and optimization of security strategies. By using smart contracts to program and manipulate data, the cross-layer security architecture of UAV system networking routing and link transmission is guaranteed, improving the identification and threat assessment capabilities of network layer composite interference, and ensuring the intrinsic security of the UAV system across the network and transport layers.

[0037] The solution provided by this invention uploads node traffic information to the blockchain. Due to the blockchain network's characteristics of mutual trust consensus, tamper-proof nature, and traceability, each node can obtain information from other nodes within the cluster, achieving information sharing. By periodically calling a smart contract for malicious routing interruption identification, the system detects the sending and receiving traffic information of each node, assesses the security of each network node, and achieves secure communication between nodes. Through smart contract technology, routing interruption attacks can be effectively detected, providing security guarantees for network security. This technology has broad application prospects in areas such as network security monitoring and attack defense, contributing to the construction of a more secure and reliable network environment.

[0038] A smart contract is an automated contract based on blockchain technology. It replaces legal language with computer language to record terms and automatically executes those terms through a program. In short, a smart contract is a program that automates the traditional contract processing through computer instructions. The purpose of smart contracts is to ensure the trustworthy execution of contracts and the immutability of their results without the need for a third party. Deploying a smart contract on a blockchain allows it to be executed automatically when predetermined conditions are met. The execution result is public and transparent, viewable and verifiable by all participants. Furthermore, the result is immutable; once written to the blockchain, it cannot be changed or revoked. It shifts the user's trust from third-party institutions to the contract itself, and from the participants to the code itself.

[0039] The account storing smart contracts is called a contract account. A contract account cannot directly initiate transactions to execute contracts. Smart contract execution is based on an event-triggered mechanism. An intermediate state of the smart contract is stored in the blockchain. When an external event occurs, such as an account call or automatic timer activation, the caller first executes the contract locally, retrieving the code and contract state from the blockchain to calculate the execution result. Then, the call parameters and calculation result are broadcast to the entire network for verification by all mining nodes (i.e., the drone nodes in this invention). After consensus is reached, the blocks are assembled with other transactions and recorded in the blockchain.

[0040] The combination of blockchain and smart contracts is mainly reflected in the following aspects: smart contracts adopt the consensus mechanism of blockchain, the smart contract is run by mining nodes, the program calculation results are propagated through the network and reach a consensus before being uploaded to the blockchain; the blockchain provides storage space for smart contracts, and the data in the blockchain is consensus-based and tamper-proof.

[0041] By incorporating smart contracts, an autonomous task command and control system can be built, enabling automated task verification, authorization, and execution, reducing human intervention and potential security risks. This improves task execution efficiency and promotes innovation and optimization of security strategies.

[0042] To detect routing disruption attacks within a drone swarm, the first step is to collect traffic data from the nodes within the swarm. Then, by analyzing this traffic data, the malicious attacking nodes can be identified. Considering the distributed nature and rapid changes in the network structure of drone swarm networks, it is difficult to collect network information using traditional centralized node methods. This invention solves the problems of distributed information and difficulty in information collection among network nodes by incorporating a built-in blockchain, while also providing features such as tamper-proofing, traceability, and decentralization.

[0043] II. Detailed introduction of the plan.

[0044] 1. Blockchain network data collection.

[0045] To avoid data collection failures in traditional centralized network information collection due to central node failure or disconnection between other nodes and the central node, this invention integrates a blockchain network into a drone swarm network, adopting a distributed network information collection approach. Each drone node within the swarm connects to the blockchain network, interacting with it while uploading its received traffic information. Due to the tamper-proof and traceable nature of the blockchain network, each node can obtain information from other nodes within the swarm, achieving information sharing.

[0046] Distributed information collection of drone swarms, such as Figure 3 As shown, when a drone node receives a data packet from another drone node, it records information about the previous hop node and the data packet size. Every so often, the node calls the blockchain interface to upload all traffic information for that period to the blockchain. This invention uses a method where the traffic receiving node uploads traffic information, preventing malicious nodes from tampering with the traffic information and uploading malicious data to the blockchain.

[0047] 2. Detection of attacks driven by smart contracts.

[0048] After completing the distributed information collection of the drone swarm, further analysis of the traffic information is needed to identify nodes launching malicious attacks. A smart contract is designed to utilize the traffic information in the blockchain for attack detection. Nodes in the drone swarm network periodically write traffic information into transactions and upload them to the blockchain. Simultaneously, each drone node takes turns calling the attack detection interface in the contract. The smart contract periodically checks the block records within a certain time period (i.e., the time between two smart contract calls). Based on the information uploaded by the receiving nodes, the smart contract automatically calculates the received and sent traffic information of each node during this period, such as... Figure 4 As shown.

[0049] If the transmitted traffic is less than the threshold, the drone node is identified as a node performing an interruption attack, and the identification count is incremented by one. Alternatively, if the drone node receives non-zero traffic but transmits zero traffic, that drone node is identified as a node performing an interruption attack. After identification is complete, the identification result is returned. Simultaneously, a result query interface is provided in the smart contract, allowing each drone node to query the identification result.

[0050] The above-described solution provided in this embodiment of the invention effectively prevents malicious nodes from tampering with traffic information by having the node receiving the traffic upload traffic information. The reason is as follows:

[0051] 1) If a malicious node uploads traffic information that is not from its own node, that is, the recipient in the traffic information is different from the node that uploaded the information, then the traffic information cannot pass the verification and the upload will fail.

[0052] 2) If a malicious node forges traffic information and uploads it to the blockchain, the malicious node can still be identified and judged as carrying out a routing interruption attack because there is no traffic sending information of the malicious node in the cluster.

[0053] 3) If a malicious node uploads real traffic information, then obviously, the smart contract can identify the malicious node in the cluster that is carrying out a routing interruption attack.

[0054] To facilitate understanding, the present invention will be further described below with specific examples.

[0055] In this example, Figure 2 Taking the scenario shown as an example, there are six drones in the drone swarm network, denoted as drone nodes A to D.

[0056] An effective identification scheme for receiving node data upload patterns is adopted. When drone node A receives a data packet from drone node C, it uploads the information (in the form of "form: C, to: A, xxx bits") to the blockchain. The drone node writes node traffic information to the smart contract by calling the function setNodeTraffic.

[0057] The smart contract periodically checks the block records and counts the data packets sent and received between drone nodes based on the information uploaded by the drone nodes within the period to determine whether a routing interruption has occurred. It checks the block records within a certain time period and uses the `route_identified` function to detect routing interruption attack nodes using drone node traffic information. It calculates the size of data packets sent and received between drone nodes based on the traffic information uploaded by each node. It includes the following two cases: (1) If the received traffic of a drone node is not 0 and the sent traffic is 0, then the drone node is identified as a node that has committed an interruption attack; (2) If the sent traffic of a drone node is less than the threshold, then the drone node is also identified as a drone node that has committed an interruption attack. After identification is completed, the identification result is returned. The smart contract reserves a result query interface, and drone nodes can use the `getCount` function to query the smart contract's detection history for each node.

[0058] The principles behind the above two scenarios are as follows:

[0059] (1) Assume drone node C is a malicious node, and the other drone nodes are normal nodes. When drone node C receives a data packet, it will not forward any received data packets. Therefore, there is no record in the blockchain of other drone nodes receiving data packets from drone node C. There are two scenarios for drone node C uploading data to the blockchain: The first is uploading real data: i.e., "form: A, to: C, xxx bits", indicating that drone node C received a data packet from drone node A. The other drone nodes will not receive data packets sent by drone node C, i.e., the send data packet is 0, thus identifying drone node C as a malicious node; The second is uploading fake data: i.e., "from: A, to: C, 0 bits". The other drone nodes will also not receive data packets forwarded by C. That is, drone node C receives 0 data packets and sends 0 data packets, thus identifying drone node C as a malicious node. It can be seen that regardless of whether the information uploaded by drone node C is true or false, it can be identified as a malicious node.

[0060] (2) When drone node C does not forward any data packets, the smart contract counts that it has sent 0 data packets and determines that it is a malicious node. When drone node C simply does not forward data packets from a specific node (such as drone node A), there are two situations for drone node C's data being uploaded to the blockchain: If drone node C uploads real information, then similar to the previous situation, the smart contract counts that the data packets it sends are less than the threshold and determines that it is a malicious node; as an example, the threshold can be set to half of the received traffic, and sending traffic less than the threshold means that the sent traffic is much less than the received traffic.

[0061] Through the above description of the embodiments, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of the above embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.), including several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0062] Example 2

[0063] This invention also provides a system for identifying malicious routing disruption attacks in drone swarm networks. This system is primarily used to implement the methods provided in the aforementioned embodiments. The system mainly includes: a blockchain network and a drone swarm network; the blockchain network deploys smart contracts, and the drone swarm network contains multiple drone nodes; wherein:

[0064] The blockchain network is integrated with the drone swarm network. Each drone node in the drone swarm network is connected to the blockchain network and uploads its received traffic information to the blockchain network.

[0065] In a drone swarm network, drone nodes take turns calling smart contracts in the blockchain network to identify malicious routing interruption attacks. The smart contract checks the block records in the blockchain network over a period of time, calculates the received and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies nodes that are maliciously interrupting traffic attacks.

[0066] In this embodiment of the invention, uploading its own received traffic information to the blockchain network includes: after each drone node receives a data packet sent by another drone node, it records the drone node ID that sent the data packet, its own ID, and the relevant data packet, and uploads them to the blockchain network as received traffic information.

[0067] In this embodiment of the invention, the smart contract includes an attack detection interface and a result query interface; wherein, the drone node identifies malicious routing interruption attacks by calling the attack detection interface of the smart contract; and the drone node queries the results of the malicious routing interruption attack identification by calling the result query interface of the smart contract.

[0068] In this embodiment of the invention, the step of calculating the received traffic information and sent traffic information of each drone node within a certain period of time based on the received traffic information uploaded by each drone node, and identifying malicious routing interruption attack nodes in this way, includes: if the received traffic of a drone node is not 0 and the sent traffic is 0, then the corresponding drone node is judged as a malicious routing interruption attack node; or, if the sent traffic of a drone node is less than a threshold, then the corresponding drone node is judged as a malicious routing interruption attack node.

[0069] Since the technical details involved in the above system have been described in detail in the previous embodiment 1, they will not be repeated here.

[0070] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the system can be divided into different functional modules to complete all or part of the functions described above.

[0071] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for identifying malicious routing disruption attacks in unmanned aerial vehicle (UAV) swarm networks, characterized in that, include: The blockchain network is integrated with the drone swarm network, in which each drone node is connected to the blockchain network and uploads its received traffic information to the blockchain. In the drone swarm network, drone nodes take turns calling the smart contract in the blockchain network to identify malicious routing interruption attacks. The smart contract checks the block records in the blockchain network over a period of time, calculates the received and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies the malicious routing interruption attack nodes accordingly. The smart contract includes an attack detection interface and a result query interface; wherein, the drone node identifies malicious routing interruption attacks by calling the attack detection interface of the smart contract; and the drone node queries the results of the malicious routing interruption attack identification by calling the result query interface of the smart contract.

2. The method for identifying malicious routing disruption attacks in a drone swarm network according to claim 1, characterized in that, Uploading its own received traffic information to the blockchain network includes: After receiving a data packet from another drone node, each drone node records the drone node ID that sent the data packet, its own ID, and the relevant data packet, and uploads them to the blockchain network as received traffic information.

3. The method for identifying malicious routing disruption attacks in a drone swarm network according to claim 1, characterized in that, The process involves calculating the received and transmitted traffic information of each drone node over a certain period based on the received traffic information uploaded by each drone node, and using this information to identify malicious routing interruption attack nodes, including: If the received traffic of a drone node is not 0 and the sent traffic is 0, the corresponding drone node will be identified as a malicious routing interruption attack node. Alternatively, if the traffic sent by a drone node is less than the threshold, the corresponding drone node will be identified as a malicious routing interruption attack node.

4. A system for identifying malicious routing disruption attacks in unmanned aerial vehicle (UAV) swarm networks, characterized in that, include: Blockchain networks and drone swarm networks; The blockchain network deploys smart contracts, and the drone swarm network contains multiple drone nodes; among them: The blockchain network is integrated with the drone swarm network. Each drone node in the drone swarm network is connected to the blockchain network and uploads its received traffic information to the blockchain network. In the drone swarm network, drone nodes take turns calling the smart contract in the blockchain network to identify malicious routing interruption attacks. The smart contract checks the block records in the blockchain network over a period of time, calculates the received and sent traffic information of each drone node over a period of time based on the received traffic information uploaded by each drone node, and identifies the malicious routing interruption attack nodes accordingly. The smart contract includes an attack detection interface and a result query interface; wherein, the drone node identifies malicious routing interruption attacks by calling the attack detection interface of the smart contract; and the drone node queries the results of the malicious routing interruption attack identification by calling the result query interface of the smart contract.

5. A system for identifying malicious routing disruption attacks in a drone swarm network according to claim 4, characterized in that, Uploading its own received traffic information to the blockchain network includes: After receiving a data packet from another drone node, each drone node records the drone node ID that sent the data packet, its own ID, and the relevant data packet, and uploads them to the blockchain network as received traffic information.

6. A system for identifying malicious routing disruption attacks in a drone swarm network according to claim 4, characterized in that, The process involves calculating the received and transmitted traffic information of each drone node over a certain period based on the received traffic information uploaded by each drone node, and using this information to identify malicious routing interruption attack nodes, including: If the received traffic of a drone node is not 0 and the sent traffic is 0, the corresponding drone node will be identified as a malicious routing interruption attack node. Alternatively, if the traffic sent by a drone node is less than the threshold, the corresponding drone node will be identified as a malicious routing interruption attack node.

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