Byzantine Robot Recognition Scheme via Blockchain-Based Reputation Management
HUANG Jie1,2, ZENG Jiazhou1,2
1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108; 2. 5G+ Industrial Internet Institute, Fuzhou University, Fuzhou 350108
Abstract A reputation management system with identity authentication and task supervisor (RMS-IATS) for swarm robotics via blockchain technology is proposed to identify Byzantine robots within the swarm robotics and avoid the security threat caused by Byzantine robots to swarm robotics. Firstly, a classical blockchain-based swarm robotics reputation management system(RMS) is improved by introducing penalty factors, and a severer reputation value penalty is imposed on the robotics with long-term Byzantine behavior. Secondly, to speed up the identification of Byzantine robots within swarm robotics, an identity authentication protocol is devised, and thus lower initial reputation scores are assigned to the robots with unauthorized identities. Next, a dual-layer communication network for communication between robots is designed to solve the communication latency issue caused by blockchain in the swarm robotics system. Finally, the feasibility of the proposed blockchain-based RMS-IATS and dual-layer communication network is proved through simulations. The identification time for different types of Byzantine robots is shortened by RMS-IATS compared with the classical RMS for swarm robotics, and the maximum communication latency of the system is reduced by the proposed dual-layer communication network compared with the blockchain.
[1] 郭笛,谢旦岚,纪媛.多重约束下智慧仓储机器人配置仿真优化研究.系统仿真学报, 2020, 32(10): 2066-2072. (GUO D, XIE D L, JI Y.Research on Simulation Optimization of Intelligent Storage Robot Configuration under Multiple Constraints. Journal of System Simulation, 2020, 32(10): 2066-2072.) [2] LI Y Z.Research on Multi-AGVs Cooperative Transportation Stra-tegy in Warehouse Logistics Environment Based on HCA Algorithm // Proc of the IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms. Washington, USA: IEEE, 2023: 1753-1758. [3] LI H, SAVKIN A V.Wireless Sensor Network Based Navigation of Micro Flying Robots in the Industrial Internet of Things. IEEE Transactions on Industrial Informatics, 2018, 14(8): 3524-3533. [4] MEIKE D, PELLICCIARI M, BERSELLI G.Energy Efficient Use of Multirobot Production Lines in the Automotive Industry: Detailed System Modeling and Optimization. IEEE Transactions on Automation Science and Engineering, 2014, 11(3): 798-809. [5] 薛颂东,张云正,曾建潮.目标围捕任务中搜索与预包围阶段的群机器人行为学习.模式识别与人工智能, 2018, 31(4): 370-378. (XUE S D, ZHANG Y Z, ZENG J C.Swarm Robotic Behaviour Learning in Search and Pre-Surround Stage for Targets Trapping Taskd. Pattern Recognition an Artificial Intelligence. 2018, 31(4): 370-378.) [6] YANG J X.Multi-robot Coordination for Environment Exploration and Patrol. Journal of Physics(Conference Series), 2022, 2402. DOI: 10.1088/1742-6596/2402/1/012041. [7] MOKHTAR A, MURPHY N, BRUTON J.Blockchain-Based Multi-robot Path Planning // Proc of the IEEE 5th World Forum on Internet of Things. Washington,USA: IEEE, 2019: 584-589. [8] PUTRA G D, DEDEOGLU V, KANHERE S S, et al. Blockchain for Trust and Reputation Management in Cyber-Physical Systems // TRAN D A, THAI M T, KRISHNAMACHARI B, eds. Handbook on Blockchain. Berlin, Germany: Springer, 2022: 339-362. [9] ZIKRATOV I, MASLENNIKOV O, LEBEDEV I, et al. Dynamic Trust Management Framework for Robotic Multi-agent Systems // Proc of the International Conference on Next Generation Wired/Wireless Networking. Berlin,Germany: Springer, 2016: 339-348. [10] WATANABE Y.A Proposal of Distributed Occupancy Grid Map on Block Chain Network // Proc of the 17th International Symposium on Web and Wireless Geographical Information Systems. Berlin, Germany: Springer, 2019: 150-159. [11] LI J N, WU J, LI J H, et al. Blockchain-Based Trust Edge Know- ledge Inference of Multi-robot Systems for Collaborative Tasks. IEEE Communications Magazine, 2021, 59(7): 94-100. [12] STROBEL V, FERRER E C, DORIGO M.Managing Byzantine Robots via Blockchain Technology in a Swarm Robotics Collective Decision Making Scenario // Proc of the 17th International Confe-rence on Autonomous Agents and Multi-agent Systems. New York,USA: ACM, 2018: 541-549. [13] STROBEL V, DORIGO M.Blockchain Technology for Robot Swarms: A Shared Knowledge and Reputation Management System for Collective Estimation // Proc of the 11th International Conference on Swarm Intelligence. Berlin,Germany: Springer, 2018: 425-426. [14] LUO J, DING B, XU J.Filtering Inconsistent Failure in Robot Collective Decision with Blockchain // Proc of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Washington,USA: IEEE, 2019: 577-582. [15] STROBEL V, FERRER E C, DORIGO M.Blockchain Technology Secures Robot Swarms: A Comparison of Consensus Protocols and Their Resilience to Byzantine Robots. Frontiers in Robotics and AI, 2020, 7. DOI: 10.3389/frobt.2020.00054. [16] FERRER E C, JIMÉNEZ E, LOPEZ-PRESA J L, et al. RFollowing Leaders in Byzantine Multirobot Systems by Using Blockchain Technology. IEEE Transactions on Robotics, 2022, 38(2): 1101-1117. [17] HUANG J, ZHOU N, CAO M.RAdaptive Fuzzy Behavioral Control of Second-Order Autonomous Agents with Prioritized Missions: Theory and ExperimentsR. IEEE Transactions on Industrial Electro-nics, 2019, 66(12): 9612-9622. [18] 刘明达,陈左宁,拾以娟,等.区块链在数据安全领域的研究进展.计算机学报, 2021, 44(1): 1-27. (LIU M D, CHEN Z N, SHI Y J, et al. Research Progress of Blockchain in Data Security. Chinese Journal of Computers, 2021, 44(1): 1-27.) [19] FERRER E C.The Blockchain: A New Framework for Robotic Swarm Systems // Proc of the Future Technologies Conference. Berlin,Germany: Springer, 2019: 1037-1058. [20] BELLINI E, IRAQI Y, DAMIANI E.Blockchain-Based Distributed Trust and Reputation Management Systems: A Survey. IEEE Access, 2020, 8: 21127-21151. [21] ZHU C S, NICANFAR H, LEUNG V C M, et al. An Authenticated Trust and Reputation Calculation and Management System for Cloud and Sensor Networks Integration. IEEE Transactions on Information Forensics and Security, 2015, 10(1): 118-131. [22] 黄捷,李帮银,陈宇韬,等.基于区块链的群机器人数据完整性与隐私性保护.无人系统技术, 2022, 5(4): 96-108. (HUANG J, LI B Y, CHEN Y T, et al. Blockchain-Based Data Integrity and Privacy Protection for Swarm Robotics. Unmanned Systems Technology, 2022, 5(4): 96-108.) [23] ESFAHANI A, MANTAS G, MATISCHEK R, et al. A Lightweight Authentication Mechanism for M2M Communications in Industrial IoT Environment. IEEE Internet of Things Journal, 2019, 6(1): 288-296. [24] XU Z S, XU C, LIANG W, et al. A Lightweight Mutual Authentication and Key Agreement Scheme for Medical Internet of Things. IEEE Access, 2019, 7: 53922-53931. [25] SUN Z J, ZHANG G Q, LU Y, et al. Leader-Follower Formation Control of Underactuated Surface Vehicles Based on Sliding Mode Control and Parameter Estimation. ISA Transactions, 2018, 72: 15-24. [26] PINCIROLI C, TRIANNI V, O'GRADY R, et al. ARGoS: A Mo- dular, Parallel, Multi-engine Simulator for Multi-robot Systems. Swarm Intelligence, 2012, 6(4): 271-295. [27] GARATTONI L, FRANCESCA G, BRUTSCHY A,et al. Software Infrastructure for E-Puck(and TAM). Technical Report: TR/IRIDIA/2015-004. Bruxelles, Belgium: Université Libre de Bruxe-lles, 2016.
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