2023, Volume 7 Issue 4
Surveying the Effectiveness of Intrusion Detection using different Deep Learning Models
AUTHOR(S)
Bony Mathew Thomas, Shalu Shani, Christa Rose Mary John, Sebin Thomas, Binny S.
DOI: https://doi.org/10.46647/ijetms.2023.v07i04.040
ABSTRACT
The rapid expansion and progression of the internet have raised serious concerns regarding the prevalence of cyber-attacks. In order to safeguard data from malicious activities, intrusion detection systems (IDS) have emerged as effective solutions employing artificial intelligence techniques like machine learning and deep learning. This survey examines relevant literature on intrusion detection systems with a particular emphasis on the learning algorithms employed by deep learning approaches. It addresses recent deep learning research using a variety of algorithms, learning techniques, and datasets to produce an operational intrusion detection system.
Page No: 293 - 299
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How to Cite This Article:
Bony Mathew Thomas, Shalu Shani, Christa Rose Mary John, Sebin Thomas, Binny S.
. Surveying the Effectiveness of Intrusion Detection using different Deep Learning Models
. ijetms;7(4):293-299. DOI: 10.46647/ijetms.2023.v07i04.040