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A theoretical analysis of wireless localisation scamming attacks using silence mechanism

A theoretical analysis of wireless localisation scamming attacks using silence mechanism Wireless networks are prone to scamming attacks that acts as a gateway for many other attacks on the networks. The cryptographic authentication is used to identify the nodes but it is always not possible because of the overhead requirements. In this paper, we proposed a method for both detecting scamming attacks, as well as locating the positions of adversaries performing the attacks. We propose to use the spatial correlation of received signal strength (RSS) to detect the scamming attacks and support vector machines (SVMs) to improve the accuracy of number of attackers. We evaluated our techniques through two networks as standard 802.11 (Wi-Fi) and 802.15.4 (Zig Bee) networks. Our experiment shows that the proposed method has 90% hit rate and precision in determining the number of attackers. Our localisation results using a representative set of algorithms provide strong evidence of high accuracy of localising multiple adversaries. Keywords: wireless network security; scamming; silence mechanism; attack detection; localisation. Reference to this paper should be made as follows: Jagatheeswari, R., Bilcah Boby, C. and Maheswaran, C.P. (2017) ` using silence mechanism', Int. J. Enterprise Network Management, Vol. 8, No. 1, pp.35­44. Biographical notes: R. Jagatheeswari received her BE in Computer Science http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Enterprise Network Management Inderscience Publishers

A theoretical analysis of wireless localisation scamming attacks using silence mechanism

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Publisher
Inderscience Publishers
Copyright
Copyright © 2017 Inderscience Enterprises Ltd.
ISSN
1748-1252
eISSN
1748-1260
DOI
10.1504/IJENM.2017.083604
Publisher site
See Article on Publisher Site

Abstract

Wireless networks are prone to scamming attacks that acts as a gateway for many other attacks on the networks. The cryptographic authentication is used to identify the nodes but it is always not possible because of the overhead requirements. In this paper, we proposed a method for both detecting scamming attacks, as well as locating the positions of adversaries performing the attacks. We propose to use the spatial correlation of received signal strength (RSS) to detect the scamming attacks and support vector machines (SVMs) to improve the accuracy of number of attackers. We evaluated our techniques through two networks as standard 802.11 (Wi-Fi) and 802.15.4 (Zig Bee) networks. Our experiment shows that the proposed method has 90% hit rate and precision in determining the number of attackers. Our localisation results using a representative set of algorithms provide strong evidence of high accuracy of localising multiple adversaries. Keywords: wireless network security; scamming; silence mechanism; attack detection; localisation. Reference to this paper should be made as follows: Jagatheeswari, R., Bilcah Boby, C. and Maheswaran, C.P. (2017) ` using silence mechanism', Int. J. Enterprise Network Management, Vol. 8, No. 1, pp.35­44. Biographical notes: R. Jagatheeswari received her BE in Computer Science

Journal

International Journal of Enterprise Network ManagementInderscience Publishers

Published: Jan 1, 2017

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