Issue No. 02 - Apr.-June (2017 vol. 16)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MPRV.2017.26
Nayeem Islam , Qualcomm
Saumitra Das , Qualcomm
Yin Chen , Qualcomm
The authors present a novel approach to protecting mobile devices from malware that might leak private information or exploit vulnerabilities. The approach, which can also keep devices from connecting to malicious access points, uses learning techniques to statically analyze apps, analyze the behavior of apps at runtime, and monitor the way devices associate with Wi-Fi access points.
Malware, Mobile handsets, Runtime, Feature extraction, Computer security, Computer hacking, Monitoring
N. Islam, S. Das and Y. Chen, "On-Device Mobile Phone Security Exploits Machine Learning," in IEEE Pervasive Computing, vol. 16, no. 2, pp. 92-96, 2017.