Volume : V, Issue : I, January - 2016

Detection of Multiple Spoofing Attackers in Wireless Networks

Santosh Dange

Abstract :

Wireless spoofing attacks are easy to launch and significantly impact on the performance of networks. Although the identity of a node can be verified through cryptographic authentication and conventional security approaches. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify and not reliant on cryptography as the basis of detecting spoofing attacks, determining the number of attackers when multiple adversaries masquerading as the same node identity, localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multiclass detection problem. Cluster–based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two frameworks using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple attacks.

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Santosh Dange Detection of Multiple Spoofing Attackers in Wireless Networks International Journal of Scientific Research, Vol : 5, Issue : 1 January 2016

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