期刊
APPLIED SCIENCES-BASEL
卷 10, 期 22, 页码 -出版社
MDPI
DOI: 10.3390/app10227975
关键词
malware; model checking; formal methods; security; Android; mobile
类别
资金
- MIUR-SecureOpenNets project
- EU SPARTA project
- CyberSANE project
- E-CORRIDOR project
The increasing diffusion of mobile devices, widely used for critical tasks such as the transmission of sensitive and private information, corresponds to an increasing need for methods to detect malicious actions that can undermine our data. As demonstrated in the literature, the signature-based approach provided by antimalware is not able to defend users from new threats. In this paper, we propose an approach based on the adoption of model checking to detect malicious families in the Android environment. We consider two different automata representing Android applications, based respectively on Control Flow Graphs and Call Graphs. The adopted graph data structure allows to detect potentially malicious behaviour and also localize the code where the malicious action happens. We experiment the effectiveness of the proposed method evaluating more than 3000 real-world Android samples (with 2552 malware belonging to 21 malicious family), by reaching an accuracy ranging from 0.97 to 1 in malicious family detection.
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