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How Discover a Malware using Model Checking

Android operating system is constantly overwhelmed by new sophisticated threats and new zero-day attacks. While aggressive malware, for instance malicious behaviors able to cipher data files or lock the GUI, are not worried to circumvention users by infection (that can try to disinfect the device), there exist malware with the aim to perform malicious actions stealthy, i.e., trying to not manifest their presence to the users. This kind of malware is less recognizable, because users are not aware of their presence. In this paper we propose FormalDroid, a tool able to detect silent malicious beaviours and to localize the malicious payload in Android application. Evaluating real-world malware samples we obtain an accuracy equal to 0.94.
ACM Asia Conference on Computer and Communications Security (ASIACCS), Abu Dhabi, UAE, 2017

Autori esterni: Vittoria Nardone (Dipartimento di Ingegneria, Università degli Studi del Sannio), Antonella Santone (Dipartimento di Ingegneria, Università degli Studi del Sannio)
Autori IIT:

Tipo: Contributo in atti di convegno
Area di disciplina: Computer Science & Engineering

File: p902-martinelli.pdf

Attività: Sicurezza di dispositivi mobili