IEEE Transactions on Software Engineering - Special issue on computer security and privacy
The Giant Black Book of Computer Viruses
The Giant Black Book of Computer Viruses
Mobile Phones as Computing Devices: The Viruses are Coming!
IEEE Pervasive Computing
Securing the wireless internet
IEEE Communications Magazine
Web service description for mobile phone virus
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Intrusion detection for mobile devices using the knowledge-based, temporal abstraction method
Journal of Systems and Software
Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
WSEAS Transactions on Information Science and Applications
"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
Randomizing smartphone malware profiles against statistical mining techniques
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
LIDAR: a layered intrusion detection and remediationframework for smartphones
Proceedings of the 4th international ACM Sigsoft symposium on Architecting critical systems
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There have been cases reported for the new threats from mobile phone technologies and it has raised the awareness among the technology and antivirus vendors. Malicious programs such as Viruses, Trojan, and Worms have been created and targeted at mobile phone. This paper discusses the possible attacking model on mobile phone adapted from malicious attack on computer. It also presents the types of attack and appropriate solution model for mobile phone. A prototype of the simulation of malicious software and detection software on mobile devices is developed and the results of applying this approach to simulated malicious software and detection software on mobile device are also presented.