Anomaly detection: a soft computing approach
NSPW '94 Proceedings of the 1994 workshop on New security paradigms
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Effective Intrusion Detection Using Multiple Sensors in Wireless Ad Hoc Networks
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 2 - Volume 2
Intrusion detection techniques for mobile wireless networks
Wireless Networks
Mobility-based anomaly detection in cellular mobile networks
Proceedings of the 3rd ACM workshop on Wireless security
Application of Rough Set Theory in Network Fault Diagnosis
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Feature selection with rough sets for web page classification
Transactions on Rough Sets II
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The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal attackers - masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on this, the used pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function considering weighted feature values. The performance of our scheme is evaluated by using a simulation.