INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
ANALYSIS OF VARIOUS MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR NETWORK INTRUSION DETECTION SYSTEM
Authors Name:
Punyashree B
, Radhika K R
Unique Id:
IJSDR2307178
Published In:
Volume 8 Issue 7, July-2023
Abstract:
A wide range of cyber-attacks have been happening on daily basis. Computers are always protected against the attacks but detecting intrusion in network is always helpful in preventing attacks and protecting the system. This paper provides a comprehensive analysis of machine learning and deep learning approaches used in Network Intrusion Detection Systems (NIDS). It explores the fundamental concepts and challenges of NIDS and highlights the limitations of traditional rule-based methods. Implementing the models and analyzing which is best accepted
Keywords:
intrusion detection, cyber-attacks, deep learning, network intrusion, machine learning.
Cite Article:
"ANALYSIS OF VARIOUS MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR NETWORK INTRUSION DETECTION SYSTEM ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 7, page no.1202 - 1210, July-2023, Available :http://www.ijsdr.org/papers/IJSDR2307178.pdf
Downloads:
000338536
Publication Details:
Published Paper ID: IJSDR2307178
Registration ID:207876
Published In: Volume 8 Issue 7, July-2023
DOI (Digital Object Identifier):
Page No: 1202 - 1210
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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