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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/14106

Title: An automatic and self-adaptive multi-layer data fusion system for WiFi attack detection
Authors: Aparicio-Navarro, Francisco J.
Kyriakopoulos, Konstantinos G.
Parish, David J.
Keywords: Basic probability assignment
Data fusion
Multi-layer measurements
Spoofing attacks
Issue Date: 2013
Publisher: © Inderscience
Citation: APARICIO-NAVARRO, F.J., KYRIAKOPOULOS, K.G. and PARISH, D.J., 2013. An automatic and self-adaptive multi-layer data fusion system for WiFi attack detection. International Journal of Internet Technology and Secured Transactions, 5 (1), pp. 42 - 62.
Abstract: Wireless networks are becoming susceptible to increasingly more sophisticated threats. Most of the current intrusion detection systems (IDSs) that employ multi-layer techniques for mitigating network attacks offer better performance than IDSs that employ single layer approach. However, few of the current multi-layer IDSs could be used off-the-shelf without prior thorough training with completely clean datasets or a fine tuning period. Dempster-Shafer theory has been used with the purpose of combining beliefs of different metric measurements across multiple layers. However, an important step to be investigated remains open; this is to find an automatic and self-adaptive process of basic probability assignment (BPA). This paper describes a novel BPA methodology able to automatically adapt its detection capabilities to the current measured characteristics, without intervention from the IDS administrator. We have developed a multi-layer-based application able to classify individual network frames as normal or malicious with perfect detection accuracy. Copyright © 2013 Inderscience Enterprises Ltd.
Description: This article was published in the journal, International Journal of Internet Technology and Secured Transactions [© Inderscience] and the definitive version is available at: http://dx.doi.org/10.1504/IJITST.2013.058294
Sponsor: This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/H005005/1 ]
Version: Accepted for publication
DOI: 10.1504/IJITST.2013.058294
URI: https://dspace.lboro.ac.uk/2134/14106
Publisher Link: http://dx.doi.org/10.1504/IJITST.2013.058294
ISSN: 1748-569X
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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