通信学报 ›› 2019, Vol. 40 ›› Issue (5): 13-23.doi: 10.11959/j.issn.1000-436x.2019085

• 学术论文 • 上一篇    下一篇

APP隐私泄露风险评估与保护方案

王新宇1,2,牛犇1,李凤华1,2,贺坤1,2   

  1. 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
  • 修回日期:2019-02-28 出版日期:2019-05-25 发布日期:2019-05-30
  • 作者简介:王新宇(1989- ),男,甘肃平凉人,中国科学院信息工程研究所博士生,主要研究方向为信息保护、隐私计算。|牛犇(1984- ),男,陕西西安人,博士,中国科学院信息工程研究所副研究员,主要研究方向为网络安全、隐私计算。|李凤华(1966- ),男,湖北浠水人,博士,中国科学院信息工程研究所研究员、博士生导师,主要研究方向为网络与系统安全、信息保护、隐私计算。|贺坤(1995- ),男,安徽安庆人,中国科学院信息工程研究所硕士生,主要研究方向为信息保护、隐私计算。
  • 基金资助:
    国家重点研发计划基金资助项目(2017YFB0802203);国家自然科学基金资助项目(U1401251);国家自然科学基金资助项目(61672515);国家自然科学基金资助项目(61872441);中国科学院青年创新促进会人才基金资助项目;工业和信息化部2018工业互联网创新发展工程基金资助项目;工业互联网标识解析数据管理技术标准制定与试验验证

Risk assessing and privacy-preserving scheme for privacy leakage in APP

Xinyu WANG1,2,Ben NIU1,Fenghua LI1,2,Kun HE1,2   

  1. 1 Institute of Information Engineering,Chinese Academy of Sciences,Beijing 100093,China
    2 School of Cyber Security,University of Chinese Academy of Sciences,Beijing 100049,China
  • Revised:2019-02-28 Online:2019-05-25 Published:2019-05-30
  • Supported by:
    The National Key Research and Development Program of China(2017YFB0802203);The National Natural Science Foundation of China(U1401251);The National Natural Science Foundation of China(61672515);The National Natural Science Foundation of China(61872441);Youth Innovation Promotion Association CAS,;Industrial Internet Innovation and Development Project of China;Technical Standard Formulation and Verification of Identifier Data Management for Identification and Resolution System

摘要:

针对APP中第三方服务提供商非法采集用户隐私信息的问题,提出了一种APP隐私信息泄露风险评估方案PRAS。该方案通过统计第三方服务提供商从不同APP获取的权限,并考虑权限组合对隐私泄露风险带来的非线性影响,构建模型来评估隐私泄露风险。基于风险评估结果,在服务质量与隐私保护之间进行均衡分析,最终给出系统整体的权限管理方案,在保证服务质量的同时,降低隐私信息泄露风险。实验结果表明,PRAS将APP整体的隐私泄露风险平均降低了18.5%。

关键词: 安卓, 隐私保护, 风险评估, 权限管理

Abstract:

The APP in smartphone contain various third-party services.However,the service providers illegally read the user’s private information.To address this problem,a privacy risk assessing scheme called PRAS was proposed.Firstly,a model was built to assess the risk of privacy leakage,by counting all the permissions acquired by each service providers and considering the non-linear impact of the permissions combination on privacy leakage.Then,by analyzing the balance between service quality and privacy-preserving,an optimal model was used to minimized the risk of private information leakage,and a permission management method was given to protect the privacy information among APP.The experiment results show that PRAS reduces the risk of privacy leakage by an average of 18.5%.

Key words: Android, privacy-preserving, risk assessment, permission management

中图分类号: 

No Suggested Reading articles found!