Title:	WIRELESS INTRUSION DETECTION SYSTEM ON THE BASIS OF DATA MINING METHODS
Author(s):	Ilya Sharabyrov, Vladimir Vasilyev, Murat Guzairov, Irina Mashkina
ISBN:	978-989-8533-56-2
Editors:	Hans Weghorn
Year:	2016
Edition:	Single
Keywords:	Intrusion detection system, Data mining, Classification model, Wi-Fi wireless network, Network traffic parameters vector, Ensemble of algorithms
Type:	Full Paper
First Page:	43
Last Page:	50
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	Nowadays wireless networks, including local ones, continue to evolve rapidly due to their accessibility, simplicity to connect/add users, and proliferation of mobile devices. However, wireless transmission medium due to its features may provide potential conditions for network traffic eavesdropping and unauthorized access to the wireless network by intruders located in the service area. Moreover, such networks can be exposed to multiple types of attacks. For this reason companies using a wireless transmission medium should implement a complex data security system, the intrusion detection systems being one of the relevant methods of preventing wireless attacks. At the same time, to perform the analysis of network traffic parameters for the signs of attack, data mining methods can be used due to their vast possibilities. This paper attempts to provide an overview of network attacks that are relevant to local wireless networks, and presents an architecture of the intrusion detection system based on data mining techniques, as well as a comparison of these techniques in detecting the above-mentioned attacks. In accordance with the experimental results, an ensemble approach to detecting attacks in local wireless networks is proposed.
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