Traffic characteristic based privacy leakage assessment scheme for Android device

Zhu WANG; Kun HE; Xinyu WANG; Ben NIU; Fenghua LI

doi:10.11959/j.issn.1000-436x.2020020

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Traffic characteristic based privacy leakage assessment scheme for Android device

Papers | 更新时间：2024-06-05

- Traffic characteristic based privacy leakage assessment scheme for Android device
- Journal on Communications Vol. 41, Issue 2, Pages: 155-164(2020)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2017YFB0802203);The National Natural Science Foundation of China(61872441);The National Natural Science Foundation of China(61672515);Youth Innovation Promotion Association CAS(2018196)
- DOI：10.11959/j.issn.1000-436x.2020020
  CLC： TN929
- Online First：2020-02，
  
  Published：25 February 2020
- 稿件说明：
移动端阅览
Zhu WANG, Kun HE, Xinyu WANG, et al. Traffic characteristic based privacy leakage assessment scheme for Android device[J]. Journal on Communications, 2020, 41(2): 155-164.
DOI：

Zhu WANG, Kun HE, Xinyu WANG, et al. Traffic characteristic based privacy leakage assessment scheme for Android device[J]. Journal on Communications, 2020, 41(2): 155-164. DOI： 10.11959/j.issn.1000-436x.2020020.

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HostRisk。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。

Abstract

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.

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references

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