X-Decaf:Android平台社交类应用的缓存文件泄露检测
发布时间：2018-11-27 18:08
【摘要】：由于社交类应用涉及的隐私数据类型非常多,导致这类应用在被广泛使用的同时,频繁出现用户隐私泄露事件,但是目前还鲜有针对社交应用的隐私泄露检测机制的研究。该文结合Android系统的特性,提出一个面向Android社交类应用检测框架X-Decaf(Xposed-based-detecting-cache-file),创新性地利用污点追踪技术以及Xposed框架,获取应用内疑似泄露路径,监测隐私数据的缓存文件。此外,该文给出了对隐私泄露进行评级的建议,并利用该框架对50款社交类应用进行了检测,发现社交类应用普遍存在泄露用户隐私信息的漏洞。
[Abstract]:Because there are many types of privacy data involved in social applications, such applications frequently occur user privacy disclosure events while they are widely used. However, there are few researches on the detection mechanism of privacy leaks in social applications. Based on the characteristics of Android system, this paper proposes a detection framework X-Decaf (Xposed-based-detecting-cache-file) for Android social applications, which makes innovative use of stain tracing technology and Xposed framework to obtain suspected leak paths in applications. Cache files that monitor privacy data. In addition, this paper gives the suggestion of rating privacy disclosure, and uses the framework to detect 50 social applications, and finds that social applications generally exist vulnerabilities of revealing user privacy information.
【作者单位】： 北京邮电大学计算机学院;
【基金】：国家自然科学基金资助(61370195) 中兴通讯产学研项目~~
【分类号】：TP309
[Abstract]:Because there are many types of privacy data involved in social applications, such applications frequently occur user privacy disclosure events while they are widely used. However, there are few researches on the detection mechanism of privacy leaks in social applications. Based on the characteristics of Android system, this paper proposes a detection framework X-Decaf (Xposed-based-detecting-cache-file) for Android social applications, which makes innovative use of stain tracing technology and Xposed framework to obtain suspected leak paths in applications. Cache files that monitor privacy data. In addition, this paper gives the suggestion of rating privacy disclosure, and uses the framework to detect 50 social applications, and finds that social applications generally exist vulnerabilities of revealing user privacy information.
【作者单位】： 北京邮电大学计算机学院;
【基金】：国家自然科学基金资助(61370195) 中兴通讯产学研项目~~
【分类号】：TP309
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