Evolution and Performance Analysis of Multiple Spoofing Attackers in Wireless Networks
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 2
Abstract
Spoofing attack is an identity based attack through which a malicious user can spoof the MAC address of an node to create multiple illegitimate identities that highly affect the performance of wireless sensor network. The identification of spoofing attackers, determining the number of attackers, localizing multiple adversaries and eliminating them is a challenging task in Wireless Sensor Network. The K-Means clustering approach is used to detect the spoofing attackers and localize them. This approach did not predict the attackers accurately. To overcome this problem, this paper proposes Chronological Likelihood Fraction Test (CLFT) as a fast and effective mobile replica node detection scheme to detect the spoofing attackers when the node is fixed or in movement. In addition, it uses the inherited spatial correlation of Received Signal Strength (RSS) from wireless nodes to detect the spoofing attacks. It formulates the problem of determining the number of attackers as a multi class detection problem. The Support Vector Machines (SVM) method is used to train the data to further improve the accuracy of determining the number of attackers. Analytical and simulation experiments result shows that the proposed scheme detects the attackers in Wireless Sensor Network in an efficient and robust manner at the cost of reasonable overheads.
Authors and Affiliations
P. Kiruthika Devi, Dr. R. Manavalan
Keywords
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