Detecting Permission Over-claim of Android Applications with Static and Semantic Analysis Approach

Junwei Tang, Ruixuan Li, Hongmu Han, Heng Zhang, X. Gu
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引用次数: 11

Abstract

Android access control granularity based on its permission mechanism is relatively coarse, which cannot effectively protect the user privacy. Many Android applications do not strictly abide by the principle of least privilege (PLP). Both benign and malicious apps may request more permissions than those they really use. We rethink previous permission over-claim problem of Android applications, and extend it to three kinds of problems: Explicit Permission Over-claim, Implicit Permission Over-claim and Ad Library Permission Over-claim. The latter two problems are new that have not been raised by any previous work. Static analysis is to decompile the applications to generate intermediate code and then analyze the usage of permissions. Our static analysis on 10710 applications shows that 76.08% of them may have Explicit Permission Over-claim problem, among those there are 424 applications that have sensitive permissions, which are only used in the advertisement library’s code of the applications rather than developer’s own code. They have Ad Library Permission Over-claim problem. The main idea of our semantic analysis is to calculate the semantic similarity between apps’ descriptions and function phrases. If the similarity exceeds a certain threshold, the app is considered relevant to the corresponding function. We compare the results of the semantic analysis with those of manual reading of 102 Android application descriptions. The F-measures of the three chosen functions are 80.82%, 70.48% and 89.62%, respectively. The evaluation results show our method can efficiently detect the above three kinds of permission over claim problems which indicates that our method would be helpful for normal users to have a clear understanding of permission usage of Android applications.
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基于静态和语义分析方法的Android应用权限过度检测
Android基于其权限机制的访问控制粒度比较粗,无法有效保护用户隐私。许多Android应用程序并不严格遵守最小特权原则(PLP)。良性和恶意应用程序都可能请求比它们实际使用的权限更多的权限。我们重新思考以往Android应用的权限过求问题,并将其扩展为三类问题:显性权限过求、隐性权限过求和广告库权限过求。后两个问题是新的,以前的工作没有提出过。静态分析是对应用程序进行反编译,生成中间代码,然后分析权限的使用情况。我们对10710个应用进行了静态分析,其中76.08%的应用可能存在显式权限过度请求问题,其中有424个应用具有敏感权限,这些敏感权限仅在应用的广告库代码中使用,而不是开发者自己的代码中使用。他们有广告库许可索赔过多的问题。我们的语义分析的主要思想是计算应用描述和功能短语之间的语义相似度。如果相似性超过一定的阈值,则认为该应用与相应的功能相关。我们将语义分析结果与手工阅读102个Android应用描述的结果进行了比较。所选函数的f值分别为80.82%、70.48%和89.62%。评估结果表明,我们的方法可以有效地检测出上述三种权限请求问题,这表明我们的方法有助于普通用户对Android应用的权限使用情况有一个清晰的认识。
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