PERFORMANCE EVALUTION OF SOFT COMPUTING TECHNIQUE BASED INTRUSION DETECTION SYSTEM.
Akanksha verma
, Reader and Head Preeti Tuli
Department of Computer Science and Engineering, DIMAT Raipur (C.G.), India
Department of Computer Science and Engineering, DIMAT Raipur (C.G.), India
Vol. 2, Issue 8 pp. 92-97 🌐 Open Access
ABSTRACT
Intrusion detection is the act of detecting undesirable activity on a system or a gadget. Labeled datasets play a major role as the process of validating and evaluating a machine learning techniques in intrusion detection systems through the survey we adopt NSL-KDD dataset (an improve version of KDD’99). Usually these data contain lots of irrelevant or redundant features. To improve the efficiency of IDS, relevant features are necessary to be extracted from original data onto feature selection approaches. In this paper, the genetic algorithm, neural network and PSO are analyzed deeply. This research paper presents the thorough survey of algorithms for detection of unwanted traffic on a network.
Keywords:
IDS; Genetic algorithm; Neural networks; PSO
