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作 者:王云涛 苏洲[1] 许其超 刘怡良 彭海霞 栾浩 WANG Yuntao;SU Zhou;XU Qichao;LIU Yiliang;PENG Haixia;LUAN Hao(School of Cyber Science and Engineering,Xi'an Jiaotong University,Xi’an 710049,China;School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China)
机构地区:[1]西安交通大学网络空间安全学院,陕西西安710049 [2]上海大学机电工程与自动化学院,上海200444
出 处:《通信学报》2023年第12期1-14,共14页Journal on Communications
基 金:国家自然科学基金资助项目(No.62302387,No.62273223,No.U23A20276,No.62101429);博士后创新人才支持计划基金资助项目(No.BX20230282)。
摘 要:针对群智协作频谱感知中恶意感知终端的投毒与搭便车攻击,结合事前威慑与事后惩罚机制提出了一种基于审计博弈的新型防御方案。首先,考虑审计预算约束,构建了一种不完全信息下的混合策略审计博弈模型,在协作感知前设置惩罚策略威慑恶意协作者,并在感知数据融合后进行审计进而实施惩罚。其次,设计了链上链下协同的轻量审计区块链模型,其中,审计证据存储在链下数据仓库,其元数据公开发布在审计链上。再次,设计了基于强化学习的分布式智能审计算法,以在动态环境下自适应地计算审计博弈的渐近混合策略均衡。仿真结果表明,相比传统方案,所提方案能快速获取稳定且渐近最优的审计策略,并积极抑制恶意协作者的投毒与搭便车行为。To defend against poisoning attacks and free-riding attacks conducted by malicious sensing terminals in crowd sensing-based collaborative spectrum sensing(CCSS),a novel audit game-based defense scheme was proposed,which combined the pre-deterrence and post-punishment mechanisms.Firstly,considering the audit budget constraint,a mixed-strategy audit game model under incomplete information was designed,which set a penalty strategy to deter mali-cious collaborators before spectrum sensing,and audited and punished them after the fusion of sensing data.Then,a lightweight audit chain model with on-chain and off-chain collaboration was designed,in which audit evidence was stored in an off-chain data warehouse and its metadata was publicly published on the blockchain.Furthermore,a distrib-uted and intelligent audit algorithm based on reinforcement learning was devised to adaptively seek the approximate mix-strategy equilibrium of the audit game.Simulation results demonstrate that the proposed scheme can quickly obtain the stable and approximately optimal audit strategies and actively suppress the poisoning and free-riding behaviors of malicious collaborators,in comparison with conventional schemes.
分 类 号:TN92[电子电信—通信与信息系统]
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