Classification of Mobile Malware
Classification of Mobile Malware with the Help of Machine Learning Techniques
Motivation: Recent rise of malware targeting mobile devices has encouraged security researchers to invent novel approaches defending against these threats. In the mobile network, we do not observer only viruses and trojan horses known from the prior era of Internet, but also new collections of malware families threatening the mobile functionalities like calls or Short Message Service (SMS). Therefore, many anti-virus companies gather and examine mobile malware and extract typical patterns reflecting its origin and purpose. These patterns help the security researcher better understand the relations between respective mobile samples.
Thesis: This thesis shall either improve the existing techniques used for identification of patterns or combine some non-standard classification and clustering techniques into a novel algorithm which will identify more specific malware families than were previously recognized by anti-virus companies.