摘要
针对现有物联网(IoT)信任度评估方法未考虑信任的时效性、非入侵因素对直接信任度评估的影响以及缺乏对推荐节点可靠度的评估,造成信任评估准确度低且不能有效应对节点恶意行为的不足,提出一种IoT节点动态信任度评估方法(IDTEM)。首先,设计节点服务质量持续因子评估节点行为,并采用动态信任衰减因子表达信任的时效性,改进基于贝叶斯的直接信任度评估方法;其次,从推荐节点价值、评价离散度与节点自身的信任度值三个方面评估推荐节点可靠度,并据此优化推荐信任度权重计算方法;同时,设计推荐信任反馈机制,通过服务提供节点完成服务后的实际信任度与推荐信任度的反馈误差实现对协同恶意推荐节点的惩罚;最后,基于熵计算节点自适应权重,得到节点综合信任度值。实验结果表明,同基于贝叶斯理论的面向无线传感器网络的信誉信任评估框架(RFSN)模型及基于节点行为的物联网信任度评估方法(BITEM)相比,IDTEM可较好地识别恶意服务和抑制恶意推荐行为,且具有较低的传输能耗。
In order to solve the problem that the existing Internet of Things(IoT)trust evaluation method ignores the impact of the timeliness of trust and non-intrusion factors on direct trust evaluation,and is lack of reliability evaluation of trust recommendation nodes,which lead to low trust evaluation accuracy and low capability to deal with malicious nodes,an IoT node Dynamic Trust Evaluation Method(IDTEM)was proposed.Firstly,the quality of service persistence factor for nodes was introduced to evaluate node behavior and the dynamic trust attenuation factor of nodes was used to express the timeliness of trust,improving the Bayesian-based direct trust evaluation method.Secondly,the reliability of recommended node was evaluated from three aspects:recommended node value,evaluation difference and trust value of the node itself,and was used to optimize the recommendation trust weight calculation method.At the same time,recommendation trust feedback mechanism was designed to suppress collaborative malicious recommendation nodes by the feedback error between the actual trust of the service provided node after providing service and the recommendation trust.Finally,the adaptive weights of direct and recommendation trust of the node were calculated based on the entropy to obtain the comprehensive trust value of the node.Experimental results show that compared with the Reputation-based Framework for high integrity Sensor Network model(RFSN)based on Bayesian theory and the Behavior-based IoT Trust Evaluation Method(BITEM),IDTEM has certain advantages in dealing with malicious services and malicious recommendation behaviors,and has lower transmission energy consumption.
作者
谢丽霞
魏瑞炘
XIE Lixia;WEI Ruixin(College of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China)
出处
《计算机应用》
CSCD
北大核心
2019年第9期2597-2603,共7页
journal of Computer Applications
基金
国家科技重大专项(2012ZX03002002)
国家自然科学基金民航联合研究基金资助项目(U1833107)
中央高校基本科研业务费资助项目(ZYGX2018028)~~
关键词
物联网
信任度评估
贝叶斯理论
推荐信任
节点相似度
Internet of Things(IoT)
trust evaluation
Bayesian theory
recommendation trust
node similarity
