International Journal of Scientific and Research Publications

IJSRP, Volume 10, Issue 5, May 2020 Edition [ISSN 2250-3153]


Hybrid Feature Selection for Network Intrusion Detection Using Data Mining
      V.Manikandan, S.Karthikeyan, Ms.T.Bhuvaneswari
Abstract: Network intrusion detection is a dynamic and important research area. It is the process of identifying malicious activity in a network by analyzing the network traffic. Data mining techniques are widely used in Intrusion Detection System (IDS) to detect anomalies. Dimensionality reduction plays a vital role in IDS, since detecting anomalies from high dimensional network traffic is time consuming process.

Reference this Research Paper (copy & paste below code):

V.Manikandan, S.Karthikeyan, Ms.T.Bhuvaneswari (2020); Hybrid Feature Selection for Network Intrusion Detection Using Data Mining; International Journal of Scientific and Research Publications (IJSRP) 10(05) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.10.05.2020.p101110
©️ Copyright 2011-2022 IJSRP - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.