ISSN No:2250-3676
Email: ijesatj@gmail.com,
Scholarly Peer Reviewed and Fully Referred Open Access Multidisciplinary Monthly Research Journal
ENHANCING INTRUSION DETECTION SYSTEMS WITH AUTOENCODER-BASED ANOMALY DETECTION IN NETWORK TRAFFICID: 1223 Abstract : |
Published:09-6-2024 Issue:Vol. 24 No. 6 (2024) Page Nos:
Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to Cite1Venkataramesh Induru,2Priyadarshini Radhakrishnan,3Vijai Anand Ramar,4Karthik Kushala,5Purandhar. N, ENHANCING INTRUSION DETECTION SYSTEMS WITH AUTOENCODER-BASED ANOMALY DETECTION IN NETWORK TRAFFIC , 2024, International Journal of Engineering Sciences and Advanced Technology, 24(6), Page , ISSN No: 2250-3676. |