普适计算中一种上下文感知的自适应可信模型  

Context-aware and self-adaptive trust model for pervasive computing

作　　者：王江涛[1,2] 陈志刚[1] 邓晓衡[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083 [2]长沙大学计算机系,湖南长沙410003

出　　处：《通信学报》2012年第11期41-48,56,共9页Journal on Communications

基　　金：国家自然科学基金资助项目(60873082;60903058);湖南省科技计划基金资助项目(2012FJ4122);长沙市科技计划基金资助项目(K1109012-71-2)~~

摘　　要：针对普适计算环境中涌现出的行为可信问题,提出了一种适合于普适计算网络环境的上下文感知的自适应可信模型CASATM,该可信模型能够自适应地对不同的服务提供不同层次的安全保障,能有效地对时间、地点、服务内容等上下文感知。同时提出了一种简单高效的风险评估模型来完成对一些完全陌生客体的可信度初始化。仿真实验表明该可信模型能有效地感知上下文并抵抗恶意客体的周期性欺骗行为。To cope with the behaviour trust problems emerging at pervasive environments, a context-aware and self- adaptive trust model（CASATM） for pervasive environments was proposed, the trust model provided security protection based on service content adaptively at various level, and be sensitive to contexts such as time, location and service con- tent. A simple and efficient risk evaluation model was presented to initialize trust value to unknown entities which was a common phenomenon in pervasive environments. Simulation results testify to the contexts awareness of this model, as well as resistance of periodically cheating behaviour from malicious entity.

关 键 词：普适计算 可信模型 上下文感知 自适应 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]