Feature Selection Using Relative Fuzzy Entropy and Ant Colony Optimization Applied to Real-time Intrusion Detection System
作者： and S. Srinivas Kumar Varma , Ravi Kiran , P. , V. Valli Kumari
DOI: 10.1016/J.PROCS.2016.05.203
关键词:
摘要: Abstract Intrusion Detection System (IDS) is one of the most important component network defense mechanism. In an attempt to detect attacks, traffic features need be identified and both attack normal data profiled. This paper proposes a set that can extracted for Real-Time Detection. also Fuzzy Entropy based heuristic Ant Colony Optimization (ACO) in-order search global best smallest Data set. The proposed feature reduction algorithm was tested on standard bench-mark UCI sets, found efficient. Further applied IDS produce promising results.
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