Trapdroid: Bare-Metal Android Malware Behavior Analysis Framework

2019 21ST INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): ICT FOR 4TH INDUSTRIAL REVOLUTION(2019)

引用 3|浏览14
暂无评分
摘要
In the realm of mobile devices, malicious applications pose considerable threats to individuals, companies and governments. Cyber security researchers are in a constant race against malware developers and analyze their new methods to exploit them for better detection. In this paper, we present TRAPDROID, a dynamic malware analysis framework mostly focused on capturing unified behavior profiles of applications by analyzing them on physical devices in real-time. Our framework processes events, which are collected from system calls, binder communications, process stats, and hardware performance counters and combines them into a simple, yet meaningful behavior format. We evaluated our framework's detection rate and performance by analyzing an up-to-date malware dataset, which also contains specially crafted applications with malicious intent. The framework is easy to use, fast and providing high accuracy in malware detection with relatively low overhead.
更多
查看译文
关键词
mobile malware, dynamic analysis, android
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要