The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detection avoidance techniques in order to hide their malicious activities from analysis tools. These include a wide range of anti-emulator techniques, where the malware programs attempt to hide their malicious activities by detecting the emulator. For this reason, countermeasures against anti-emulation are becoming increasingly important in Android malware detection. Analysis and detection based on real devices can alleviate the problems of anti-emulation as well as improve the effectiveness of dynamic analysis. Hence, in this paper we present an investigation of machine learning based malware detection using dynamic analysis on real devices. A tool is implemented to automatically extract dynamic features from Android phones and through several experiments, a comparative analysis of emulator based vs. device based detection by means of several machine learning algorithms is undertaken. Our study shows that several features could be extracted more effectively from the on-device dynamic analysis compared to emulators. It was also found that approximately 24% more apps were successfully analysed on the phone. Furthermore, all of the studied machine learning based detection performed better when applied to features extracted from the on-device dynamic analysis.
|Title of host publication||IWSPA '17: Proceedings of the 3rd ACM on International Workshop on Security And Privacy Analytics|
|Publisher||Association for Computing Machinery (ACM)|
|Number of pages||8|
|Publication status||Published - 24 Mar 2017|
|Event||ACM international workshop on security and privacy analytics, colocated with ACM CODASPY 2017, - Arizona, Scottsdale, United States|
Duration: 22 Mar 2017 → 24 Mar 2017
|Conference||ACM international workshop on security and privacy analytics, colocated with ACM CODASPY 2017,|
|Abbreviated title||IWSPA 2017|
|Period||22/03/2017 → 24/03/2017|
- Android malware
- machine learning
- malware detection
- malware analysis
- device-based detection
Alzaylaee, M. K., Yerima, S. Y., & Sezer, S. (2017). EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning. In IWSPA '17: Proceedings of the 3rd ACM on International Workshop on Security And Privacy Analytics Association for Computing Machinery (ACM).