Monitoring smartphones for anomaly detection
Mobile Networks and Applications
Intrusion detection for mobile devices using the knowledge-based, temporal abstraction method
Journal of Systems and Software
Static analysis of executables for collaborative malware detection on android
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
A framework for defending embedded systems against software attacks
ACM Transactions on Embedded Computing Systems (TECS)
"Andromaly": a behavioral malware detection framework for android devices
Journal of Intelligent Information Systems
A probabilistic diffusion scheme for anomaly detection on smartphones
WISTP'10 Proceedings of the 4th IFIP WG 11.2 international conference on Information Security Theory and Practices: security and Privacy of Pervasive Systems and Smart Devices
Defending users against smartphone apps: techniques and future directions
ICISS'11 Proceedings of the 7th international conference on Information Systems Security
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New security threats emerge against mobile devices as the devices' computing power and storage capabilities evolve. We address in this paper the issue of augmenting current intrusion detection approaches with host-based intrusion detection models for mobile devices. We show that host-based approaches are required, since network-based monitoring alone is not sufficient to encounter the future threats. We outline some of the data types on mobile devices that could be used to construct intrusion detection models, and finally propose a framework for mobile device intrusion detection.