Enhanced detection of imbalanced malicious network traffic with regularized generative adversarial networks
R Chapaneri, S Shah - Journal of Network and Computer Applications, 2022 - Elsevier
Due to the emerging network security vulnerabilities and threats, securing the network and
identifying malicious network traffic is crucial for various organizations. One critical aspect of …
identifying malicious network traffic is crucial for various organizations. One critical aspect of …
Recognition of DDoS attacks based on images correlation analysis within deep learning framework
H Jing, J Wang - Soft Computing, 2022 - Springer
Network security is of great significance in our modern society. The distributed denial of
service (DDoS) attacks is one of the most indispensable parts. This study presents a novel …
service (DDoS) attacks is one of the most indispensable parts. This study presents a novel …
Feature Based Transfer Learning Intrusion Detection System.
AM Kelani - 2023 - atrium.lib.uoguelph.ca
Recent Cyber security breaches, such as the latest T-Mobile data leak in May 2023, which
revealed the PINs, Full names, and Phone numbers of some customers, and a string of other …
revealed the PINs, Full names, and Phone numbers of some customers, and a string of other …
[PDF][PDF] Intrusion Detection Systems Using Machine Learning and Deep Learning Techniques
H Hindy - 2021 - rke.abertay.ac.uk
The increased reliance on networked technologies has led to a digital transformation of
general-and special-purpose networks that further interlace technologies and …
general-and special-purpose networks that further interlace technologies and …