Machine Learning application for intrusion detection system in network security

Machine Learning application for intrusion detection system in network security

Registration ID: IJNRD_226144

Published ID: IJNRD2408005

DOI: Click Here to Get

Satyam Gupta , Praveen Malviya

Machine Learning, intrusion detection systems(IDS), CNN, Network Security, Algorithm, ML Methodology.

This study investigates the use of machine learning (ML) to improve intrusion detection systems in the ever-changing field of network security, with findings presented through 2024. Acknowledging the shortcomings of conventional rule-based methods, the research assesses 13 intrusion detection algorithms on various datasets with an emphasis on real-world applicability, algorithmic improvements, and training/testing efficiency. The findings demonstrate a subtle trade-off between real-time detecting skills and accuracy. The analysis is noteworthy since it goes beyond 2022 and sheds light on how recent advances in algorithmic techniques affect intrusion detection. The research provides insightful advice to practitioners looking for efficient machine learning (ML)-based network security solutions by providing a thorough grasp of algorithmic performance and their applicability to modern cyberthreats.

Published Paper   E-Certificate

"Machine Learning application for intrusion detection system in network security", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 8, page no.a53-a61, August-2024, Available :https://ijnrd.org/papers/IJNRD2408005.pdf

Volume 9 Issue 8, August-2024

Pages : a53-a61

Paper Reg. ID: IJNRD_226144

Published Paper Id: IJNRD2408005

Downloads: 000121124

Research Area: Computer Science & Technology 

Country: Indore, Madhya Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2408005.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408005

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

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Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area