Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Guest Editors' Introduction: The Smart Phone--A First Platform for Pervasive Computing
IEEE Pervasive Computing
Enabling Pervasive Computing with Smart Phones
IEEE Pervasive Computing
Combining Self-Organizing Map Algorithms for Robust and Scalable Intrusion Detection
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
Static analysis of executables for collaborative malware detection on android
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
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
Modular anomaly detection for smartphone ad hoc communication
NordSec'11 Proceedings of the 16th Nordic conference on Information Security Technology for Applications
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In this paper we demonstrate how to monitor a smartphone running Symbian OS in order to extract features that describe the state of the device and can be used for anomaly detection. These features are sent to a remote server, because running a complex intrusion detection system (IDS) on this kind of mobile device still is not feasible, due to capability and hardware limitations. We give examples on how to compute some of the features and introduce the top ten applications used by mobile phone users basing on a study in 2005. The usage of these applications is recorded and visualized and for a first comparison, data results of the monitoring of a simple malware are given.