Authors :
Anand Mudhol; Prajval Sorapur; Rahul S; Sachin B M; Shilpa M.
Volume/Issue :
Volume 8 - 2023, Issue 12 - December
Google Scholar :
http://tinyurl.com/4mt76kmy
Scribd :
http://tinyurl.com/4cemp4nk
DOI :
https://doi.org/10.5281/zenodo.10499855
Abstract :
Strong Network Intrusion Detection Systems
(NIDS) are now essential for securing digital ecosystems
due to the complexity of cyber threats and the quick
growth of attack vectors. This research paper explores the
field of cybersecurity by carryingout an extensive analysis
on cutting-edge methods to improve NIDS efficacy. The
first section of the report gives a summaryof the present
threat environment and emphasizes the difficulties
presented by advanced cyberthreats. The limits of
conventional NIDS are then discussed, as well as the need
forcreative solutions to successfully handle new threats. Our
study explores the uses of cutting-edge technologies
including contrasting unsupervised and deep learning
discriminative approaches and employing a generative
adversarial network deep learning in the context of
network intrusion detection systems. Our goal in utilizing
these technologies is to improve NIDS's capacity to
identify and neutralize threats, both knownand unknown.
Strong Network Intrusion Detection Systems
(NIDS) are now essential for securing digital ecosystems
due to the complexity of cyber threats and the quick
growth of attack vectors. This research paper explores the
field of cybersecurity by carryingout an extensive analysis
on cutting-edge methods to improve NIDS efficacy. The
first section of the report gives a summaryof the present
threat environment and emphasizes the difficulties
presented by advanced cyberthreats. The limits of
conventional NIDS are then discussed, as well as the need
forcreative solutions to successfully handle new threats. Our
study explores the uses of cutting-edge technologies
including contrasting unsupervised and deep learning
discriminative approaches and employing a generative
adversarial network deep learning in the context of
network intrusion detection systems. Our goal in utilizing
these technologies is to improve NIDS's capacity to
identify and neutralize threats, both knownand unknown.
