Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
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This Author published in this journals
All Journal International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR)
Rohit Utekar
Unknown Affiliation
Humanities Civil Engineering, Building, Construction & Architecture Economics, Econometrics & Finance Education Social Sciences

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Intrusion Detection Systems Using Machine Learning. Rohit Utekar; Anuja Phapale
International Journal of Applied and Advanced Multidisciplinary Research Vol. 2 No. 1 (2024): January, 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijaamr.v2i1.550

Abstract

The utilization of machine learning to enhance Intrusion Detection Systems (IDS). It encompasses an exploration of diverse IDS categories, fundamental evaluation metrics, and the dynamic landscape of machine learning methodologies. Recent trends underscore a shift towards the adoption of deep learning techniques for improving attack detection capabilities. Challenges arise from heightened model complexity and increased resource requirements. The paper also suggests future directions that encompass the development of updated datasets and the efficient management of resources through cloud integration. Throughout, this study emphasizes the continuous demand for research and innovation in the field of cybersecurity.
Co-Authors Anuja Phapale