A Majority Voting Technique for Wireless Intrusion Detection Systems
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Authors
Alotaibi, Bandar
Issue Date
2016-04-01
Type
Presentation
Language
en_US
Keywords
Intrusion detection system , Local area network (LAN) , Medium access control (MAC) , Wireless network
Alternative Title
Abstract
This poster aims to build a misuse Wireless Local Area Network Intrusion Detection System (WIDS), and to discover some important fields in WLAN MAC-layer frame to differentiate the attackers from the legitimate devices. We tested several machine-learning algorithms, and found some promising ones to improve the accuracy and computation time on a public dataset. The Bagging classifier and our customized voting technique have good results (about 96.25% and 96.32% respectively) when tested on all the features.