云环境下基于证据理论的多服务请求隐私保护

Privacy Protection for Multiple Service Requests Based on Evidence Theory in Cloud Environment

目前云计算环境下的隐私安全研究多针对数据、用户身份及单服务请求隐私问题,对多服务请求因逻辑关联、时序披露等多维环境因素导致的隐私泄露问题缺乏完备解决方案。针对该问题,提出一种面向多云服务请求的隐私信息重要性度量方法,并基于D-S证据理论对该场景下的隐私泄漏风险进行评估,结合改进的噪声生成与混淆策略构建多云服务请求隐私保护框架。实验结果表明,在不明显增加系统开销的前提下,该方法能确保云计算环境下多服务请求的隐私安全。

Existed privacy security studies focus on privacy and security issues of data,user identity and single service request,and for the privacy leakage problem of multiple cloud service requests causing by multidimensional environment,such as factors logical association and timing series disclosures,there is no complete solution. For such problems,this paper proposes a method for measuring the importance of privacy information for multiple cloud service requests,then makes risk assessment based on D-S evidence theory for this scenario,and finally combines with the improved noise generation and obfuscation strategy to build an effective protection framework for the privacy of multiple cloud service requests. Experimental result shows that the proposed method can ensure the security of multiple cloud service requests without significantly increasing the overhead.