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作 者:舒港丽 刘一凡[1] 郭嘉宝 Shu Gangli;Liu Yifan;Guo Jiabao(School of Cyber Science and Engineering,Wuhan University,Wuhan 430000,Hubei,China)
机构地区:[1]武汉大学国家网络安全学院,湖北武汉430000
出 处:《计算机应用与软件》2024年第6期320-328,335,共10页Computer Applications and Software
基 金:国家自然科学基金联合基金项目(U1936122);中央高校基本科研业务费专项资金项目(2042017kf024);中国工程科技发展战略湖北研究院咨询研究项目(212000005);武汉市应用基础前沿项目(2018010401011295)。
摘 要:物联网节点由于所处环境复杂多变且无人监管,易受损或被捕获而成为内部攻击的源头。针对这种情况,提出基于物联网节点行为的动态综合信任评估方法。基于节点交互时的多种行为特征来计算节点的直接信任,并提出节点的自信度和推荐信任度作为权重系数参考。通过共同邻居节点获取推荐信任以缩短发现恶意节点的时间,并采用时间衰减因子和历史评估窗口来保证信任的时效性。实验结果表明,通过节点的异常行为变化能及时识别恶意节点,降低网络的能耗,具有良好的适应性和抵抗性。The nodes of the internet of things(IoT)have become the source of internal attacks due to their complex and unsupervised environment,which are easily be captured or damaged.In response to this situation,a dynamic comprehensive trust evaluation method based on the behavior of IoT nodes is proposed.This method calculated the direct evaluation value of the node based on the multiple behavior characteristics of the node during interaction,and the confidence and recommendation trust of nodes were proposed as the reference of weight coefficients.On this basis,the recommended evaluation value of the node was obtained through the common neighbor node to shorten the time for discovering malicious nodes,and the time decay factor and historical evaluation window were used to ensure the timeliness of trust.The experimental results show that the malicious nodes can be identified timely through the abnormal behavior changes of nodes,which reduces the energy consumption of the network,and has good adaptability and resistance.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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