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
A Comparison Analysis of Machine Learning Algorithms for Intrusion Detection
Authors Name:
Nishi Patwa
, Prachi Shah , Pooja Thakkar
Unique Id:
IJSDR2304140
Published In:
Volume 8 Issue 4, April-2023
Abstract:
Intrusion detection is a critical component of network security, as it helps identify potential threats and attacks on the system. The paper begins by discussing the introduction of the intrusion detection system and different types of intrusion detection systems. It then provides a comprehensive review of various machine learning algorithms, including unsupervised as well as supervised techniques. The paper also highlights the merits and demerits of various algorithms and the factors that affect their performance in intrusion detection. Finally, the paper concludes with a comparison of ML techniques used for developing IDS and summaries of relevant research articles.
"A Comparison Analysis of Machine Learning Algorithms for Intrusion Detection", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.807 - 814, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304140.pdf
Downloads:
000336256
Publication Details:
Published Paper ID: IJSDR2304140
Registration ID:205249
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.34865
Page No: 807 - 814
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
Facebook Twitter Instagram LinkedIn