UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 10 Issue 11
November-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2311418


Registration ID:
528271

Page Number

e116-e119

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Title

A Survey on Network Intrusion Detection System using Machine Learning

Abstract

The rapid evolution of the internet and communication technologies has led to a significant expansion in network size and the associated data volume. Consequently, this surge has given rise to new and sophisticated forms of cyber attacks, which present considerable challenges for maintaining the security and integrity of networks. In this context, the presence of intruders seeking to launch various malicious attacks within networks cannot be underestimated. To counteract these threats, Intrusion Detection Systems (IDS) play a pivotal role by scrutinizing network traffic to ensure the confidentiality, integrity, and availability of data. However, despite extensive research efforts, IDS still struggles with the need to enhance detection accuracy while reducing false alarm rates and addressing emerging forms of intrusions. Recently, the application of machine learning (ML) and deep learning (DL) techniques has emerged as a promising avenue to strengthen network-based IDS (NIDS) systems, aiming to detect intrusions efficiently. Machine Learning enhances NIDS by improving accuracy, adaptability to new threats, reducing false positives, and enabling the detection of complex and subtle anomalies. It also automates threat detection, reduces manual rule maintenance, and provides real-time monitoring, ultimately enhancing an organization's overall security posture.

Key Words

Deep Learning, Machine Learning, Network Anomaly Detection, Network Intrusion Detection System, Network Security

Cite This Article

"A Survey on Network Intrusion Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.e116-e119, November-2023, Available :http://www.jetir.org/papers/JETIR2311418.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Survey on Network Intrusion Detection System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppe116-e119, November-2023, Available at : http://www.jetir.org/papers/JETIR2311418.pdf

Publication Details

Published Paper ID: JETIR2311418
Registration ID: 528271
Published In: Volume 10 | Issue 11 | Year November-2023
DOI (Digital Object Identifier):
Page No: e116-e119
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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