ANALYSIS OF VARIOUS MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR NETWORK INTRUSION DETECTION SYSTEM
Punyashree B
, Radhika K R
intrusion detection, cyber-attacks, deep learning, network intrusion, machine learning.
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
"ANALYSIS OF VARIOUS MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR NETWORK INTRUSION DETECTION SYSTEM ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 7, page no.1202 - 1210, July-2023, Available :https://ijsdr.org/papers/IJSDR2307178.pdf
Volume 8
Issue 7,
July-2023
Pages : 1202 - 1210
Paper Reg. ID: IJSDR_207876
Published Paper Id: IJSDR2307178
Downloads: 000347244
Research Area: Computer Science & Technology
Country: Bangalore, karnatka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
