Major Research topic:Automated analysis of Android Malware Samples resilient to evasionAdvisor: MAGGI FEDERICO

Abstract:

Automated analysis of Android Malware Samples resilient to evasion Android is the most popular mobile Operating System (OS). Since, unlike other competitors, it enables the final user to install applications from unknown sources. For this reason, malware is a significant issue. Automated tools are needed to analyze a large volume of applications to spot malicious behaviors. In most cases, these tools use dynamic analysis, meaning that they employ techniques such as software emulation and hardware virtualization to create sandboxes where malware can be analyzed without harming the physical devices. The challenge is that modern malware can exploit imperfections to detect it is being ran in a sandbox, thus evading the analysis and concealing any malicious behaviour. Our research will focus on ways to to create systems able to analyze malware and immune to evasive techniques. The research will be divided into three main phases. In the first we want to create a system to automatically collect malware samples across different Android markets. Second, we want to analyze and classify the malware according to the evasive techniques it uses. Finally, we will design and implement (and ultimately release publicly as a web application) a system that allows people to submit applications to be analyzed in an environment immune to detection. Advisor: Stefano Zanero