Paper Title
Intrusion Detection Scheme with Dimensionality Reduction in Next Generation Networks using DenseNet
Article Identifiers
Authors
Vivek S V , Kumaraswamy S
Keywords
IDS, DensNet121
Abstract
The project endeavors to bolster network security by harnessing the power of the UNSW_NB15 dataset to construct a sophisticated Intrusion Detection System (IDS) deploying DenseNet architecture. A meticulous approach to data preprocessing unfolds, entailing nuanced techniques such as label encoding and feature scaling. The model training phase adopts advanced methodologies, notably class balancing through weight mechanisms and the integration of bespoke metrics like F1-score for rigorous evaluation. Real-time insights are facilitated by the inclusion of live plotting tools during the training process. The overarching objective of this initiative is to make substantive contributions to the realm of cybersecurity. By instating a resilient and efficient IDS, the project aspires to adeptly identify and classify a spectrum of network intrusions, thereby augmenting the overall fortitude of networks against potential threats.
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How To Cite (APA)
Vivek S V & Kumaraswamy S (April-2024). Intrusion Detection Scheme with Dimensionality Reduction in Next Generation Networks using DenseNet. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b196-b201. https://ijnrd.org/papers/IJNRD2404126.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : b196-b201
Other Publication Details
Paper Reg. ID: IJNRD_217524
Published Paper Id: IJNRD2404126
Downloads: 000121988
Research Area: Computer EngineeringÂ
Country: BANGALORE, KARNATAKA, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404126.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404126
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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