Static Analysis of Executables for Collaborative Malware Detection on Android

Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

• Type: Journal
• Year: 2009
• Where: ICC
• Authors: Aubrey-Derrick Schmidt, Rainer Bye, Hans-Gunther Schmidt, Jan Hendrik Clausen, Osman Kiraz, Kamer Ali Yüksel, Seyit Ahmet Çamtepe, Sahin Albayrak
• Keywords: Communications, ICC 2009, Malware Detection, Malware Detection Mechanisms, Smartphones