A Review on Spoofing Attack Detection in Wireless Adhoc Network
Mukesh Barapatre, Vikrant Chole, Leena H. Patil · 2013
Wireless networks are vulnerable to many identity-based attacks in which a malicious device uses forged MAC addresses to masquerade as a specific client or to create multiple illegitimate identities. Although the identity of a node can be verified through cryptographic security, conventional security approaches these are not always desirable. we propose to use spatial information, a physical property of each node, so hard to forge or alter fraudulently , and not depend on cryptographic security, on the basis for (1) detecting spoofing attacks; (2) determining the number of attackers when multiple node pretend as a same node identity, and (3) localizing multiple adversaries. We propose to use the correlation between a signal's spatial direction and the average received signal gain of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. In this paper enlist the various methods of spoofing attack detection using spatial correlation between wireless nodes. And cluster based mechanisms to determine the number of attakers in network. , we explore using Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. We evaluated techniques through two wireless adhoc networks using both an 802.11 (WiFi) network and some other wireless network standard.