Comparative Analysis of Machine Learning and Deep Learning Approaches for Intrusion  Detection Systems in Bihar

Ajit Kumar, Prof.(Dr.) Om Prakash Roy

Comparative Analysis of Machine Learning and Deep Learning Approaches for Intrusion Detection Systems in Bihar

Authors

Ajit Kumar, Prof.(Dr.) Om Prakash Roy

Keywords:

Machine Learning, Deep Learning, Intrusion Detection System, TabNet, Random Forest, XGBoost, Network Security, CIC-IDS-2018, Bihar, Cybersecurity

Abstract

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL)approaches

References

B. Madhu, M. Venu Gopala Chari, R. Vankdothu, A. K. Silivery, and V. Aerranagula, "Intrusion detection models for IOT networks via deep learning approaches," Meas. Sensors, vol. 25, p. 100641, 2023, doi: 10.1016/j.measen.2022.100641.

Downloads

Published

2024-12-20

How to Cite

Ajit Kumar, Prof.(Dr.) Om Prakash Roy. (2024). Comparative Analysis of Machine Learning and Deep Learning Approaches for Intrusion Detection Systems in Bihar . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 6966–6992. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4064