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|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|
|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|
|Publisher Link: ||http://dx.doi.org/10.1504/IJITST.2013.058294|
|Appears in Collections:||Published Articles (Mechanical, Electrical and Manufacturing Engineering)|
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