Android应用程序中潜在的组件泄漏:对恶意软件检测新功能集的调查

Li Li, Kevin Allix, Daoyuan Li, Alexandre Bartel, Tegawendé F. Bissyandé, Jacques Klein
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引用次数: 29

摘要

我们讨论了基于潜在组件泄漏(pcl)的恶意软件检测的新功能集的功能。pcl被定义为涉及Android组件间通信的敏感数据流。我们表明,pcl在Android应用程序中很常见,恶意应用程序确实比良性应用程序操纵更多的pcl。然后,我们评估了一种基于pcl的机器学习方法。实验验证显示了识别恶意软件的高性能,表明pcl可以用于区分恶意应用程序和良性应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential Component Leaks in Android Apps: An Investigation into a New Feature Set for Malware Detection
We discuss the capability of a new feature set for malware detection based on potential component leaks (PCLs). PCLs are defined as sensitive data-flows that involve Android inter-component communications. We show that PCLs are common in Android apps and that malicious applications indeed manipulate significantly more PCLs than benign apps. Then, we evaluate a machine learning-based approach relying on PCLs. Experimental validations show high performance for identifying malware, demonstrating that PCLs can be used for discriminating malicious apps from benign apps.
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