Cluster-based mechanisms in support vector machine to integrate and detect spoofing

Abstract

Wireless spoofing attack is mainly masquerades the IP address and degrade the performance of the network. In Existing an approach to address the potential spoofing attacks employ cryptographic schemes and requires key dissemination, Protection, and maintenance mechanisms. Although the cryptographic authentication approaches are not always desirable because of their overhead requirements. In this paper, Discover the presence of spoofing attack based on network adapter. Based on support vector machine (SVM) to control and prevent the malicious attacks such as an access point (AP) and denial-of-service (DOS) attack quickly. In addition, we developed the cluster-based mechanisms to improve the accuracy of determining the position of multiple attacks using localization system. The techniques can test through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Experimental results show that the proposed methods can achieve over 95 percent Hit Rate of discovering the number of attackers. Keywords--Supportvector machine (SVM), Access point (AP), Denial of service (DOS).