Artificial Neural Networks in Wireless Intrusion Detection System (ANNWIDS)
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Abstract
Intrusions are the familiar attacks in current security trend. There are several intrusion detection system enrolled so far, particularly this Intrusion Detection System (IDS) collects the data (activities) at different levels and group them accordingly. It investigates the behavior and nature of commands being executed and its severity level. It carries several layers for processing. The data to be collected and grouped as trails at first layer. The collected data to be configured at the second layer for next level of processing. The Heuristics system and Expert decision making system (EDMS) are the core processes of this approach. Heuristics system does the educated guess of incoming activity by comparing with knowledge Base (KB). Possibly it produces maximum accuracy. Depending upon this output the Expert decision making system (EDMS) does the further level of processing and take final decision. The final decisions are to be concluded based on the three basic parameters (Assurance, Ambiguity, and Divergence).This paper examines the vulnerabilities of wireless network by categorizing the intrusion.
Keywords: Intrusion, Suspicious, Neural network, Heuristics analysis, Expert system
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