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Preparation GADE and IDOL Model for Preventing Multiple Spoofing Attackers in Wireless Networks

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Document pages: 9 pages

Abstract: The Many wireless networks are susceptible to spoofing attacks. In which the identity of a node can be verified through cryptographic authentication but authentication is not always possible because it requires key management and additional infrastructural overhead. This paper propose to show that use spatial information and physical property associated with each node as hard to specifies but not reliant on cryptography, as the basis for-detecting spoofing attacks and determining the number of attackers when multiple adversaries masquerading as the same node identity and localizing multiple adversaries and need to propose the use of spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. The problem consists of determining the number of attackers as a multiclass detection problem. The cluster-based mechanisms are developed to determine the number of attackers. When the training of data are available, then using the Support Vector Machines (SVM) method to improve the accuracy of determining the number of attackers. Evaluate the techniques through two test beds using both an 802.11 (Wi-Fi) network and an 802.15.4 (ZigBee) network in two real office buildings. This experiment results show that the propose methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers and use set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries.

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