Android设备中基于流量特征的隐私泄露评估方案  

Traffic characteristic based privacy leakage assessment scheme for Android device

作　　者：王竹[1,2] 贺坤 王新宇 牛犇[1] 李凤华 WANG Zhu;HE Kun;WANG Xinyu;NIU Ben;LI Fenghua(Institute of Information Engineering,Chinese Academy of Sciences,Beijing 100093,China;School of Cyber Security,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院信息工程研究所,北京100093 [2]中国科学院大学网络空间安全学院,北京100049

出　　处：《通信学报》2020年第2期155-164,共10页Journal on Communications

基　　金：国家重点研发计划基金资助项目（No.2017YFB0802203）;国家自然科学基金资助项目（No.61872441,No.61672515）;中国科学院青年创新促进会人才基金资助项目（No.2018196)~~

摘　　要：针对Android操作系统App内第三方域名采集用户信息造成的隐私泄露问题,基于TF-IDF模型和层次聚类方法提出了移动设备中的隐私泄露评估方案Host Risk。TF-IDF模型通过App内域名的行为特征计算域名与App的业务相关性,对于未能表现出App业务相关性行为特征的业务相关域名通过平均连接的凝聚型层次聚类方法进行调整优化,最终根据App内所有域名的排名计算其隐私泄露危害程度。实验结果验证了所提方案的有效性和效率。Aiming at the privacy leakage, which was caused by collecting user information by third-party host in Android operating system App, a privacy leakage evaluation scheme HostRisk was proposed. HostRisk was based on TF-IDF model and hierarchical clustering method, which was applied in mobile device. The TF-IDF model calculated the business relevance between Apps and hosts via the behavior characteristics of the hosts in these Apps. For the business related hosts that fail to express the business relevance characteristics, those hosts were adjusted and optimized via the average connected hierarchical agglomerative clustering method. Finally, the harmful degree of privacy leakage was evaluated based on the ranking of all hosts in the App. The experimental results verify the effectiveness and efficiency of the scheme.

关 键 词：ANDROID 隐私泄露 隐私评估 隐私保护 

分 类 号：TN929[电子电信—通信与信息系统]