摘要
针对现有的信任模型不能快速有效处理WSNs中的恶意节点以及证据组合时可能会出现反直观结果问题,提出一种基于改进D-S证据理论的信任模型。分析了D-S证据理论本身存在的缺陷,定义了衡量证据间差距的焦元距离,给出了计算证据信任度的新方法。同时,修正了D-S证据理论的合成规则,设计了WSNs中识别和隔离行为不良节点的监测机制,并且对该监测机制进行了仿真分析。仿真结果表明,该机制能够快速准确地发现和隔离恶意节点,而且在一定程度上抑制了恶意节点的共谋,提高了网络的性能。同其他信任模型相比,该机制更具安全性、健壮性和准确性。
In order to solve the problem that the existing trust models could not solve malicious nodes in wireless sensor networks effectively and the problem that counter-intuitive results may appear when combining evidence,a detection scheme based on improved D-S evidence theory was proposed. The inherent deficiency of the D-S evidence theory was analyzed,a new variable was defined to describe the difference among trust evidence,and the original D-S evidence theory combination rule was modified to obtain more accurate results. Based on those improvements,a detection scheme to identify and isolate misbehaviors nodes in WSNs was proposed. Moreover,simulations were carried out to verify the effectiveness of the proposed scheme. Simulation results showed that this model could find and isolate malicious nodes quickly and accurately,suppress nodes collusion and improve network performance. Compared with other existing trust models,this model has more security,robustness and accuracy.
出处
《四川大学学报（工程科学版）》
EI
CAS
CSCD
北大核心
2016年第2期118-124,共7页
Journal of Sichuan University (Engineering Science Edition)
基金
国家自然科学基金青年基金项目资助(61402530)
陕西省自然科学基金青年项目资助(2014JQ8301)
中国博士后基金资助项目(2014M562676)
关键词
监测机制
D-S证据理论
性能仿真
信任评估
detection scheme
D-S evidence theory
performance simulation
trust evaluation
