Wireless intrusion detection based on different clustering approaches

Authors:
Athira. M. Nambiar;Asha Vijayan;Aishwarya Nandakumar
Affiliations:
Amrita Vishwa Vidyapeetham, Coimbatore, India;Amrita Vishwa Vidyapeetham, Coimbatore, India;Amrita Vishwa Vidyapeetham, Coimbatore, India
Venue:
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
Year:
2010

Citing 3
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Abstract

Wireless security is becoming an important area of product research and development. Wireless Intrusion detection Systems are commonly used in WLAN network for detecting wireless attacks. Classifiers are commonly used as detectors in these systems. Finding an efficient classifier as well selecting best set of features becomes very important for implementing these intrusion detection systems. In this paper, we are finding optimital set of features from collected WLAN data using a Ranking Algorithm technique. Then with the aid of different data mining techniques such as K-Means, self organizing map and decision tree, these features are analyzed and the performance comparison is carried out.