Article

Article title LOCAL WIRELESS NETWORKS ATTACKS DETECTION BASED ON INTELLIGENT DATA ANALYSIS
Authors V.I. Vasilyev, I.V. Sharabyrov
Section SECTION II. SECURITY OF INFORMATION SYSTEMS AND NETWORKS
Month, Year 02, 2014 @en
Index UDC 681.5:004(07)
DOI
Abstract Nowadays wireless networks, including local ones, continue to evolve rapidly. Herewith security in these networks does not often correspond to the required level. One of the most actual protection means from the wireless attacks are the intrusion detection systems. Due to the extensive spread and wide possibilities of modern data mining methods, the task of network traffic parameters analysis for the signs of attack can be solved by application of these methods. The article provides an overview of network attacks that are relevant to local wireless networks, as well as a comparison of data mining techniques, which can be used to detect the types of attacks mentioned above. The data mining techniques considered are support vector machine, k-nearest neighbor method, neural networks and decision trees. The experimental results allow making the conclusion about practical relevance of proposed approach for intrusion detection in local wireless networks.

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Keywords Wireless network; network attack; detection model; signature; Wi-Fi.
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