Boosting robustness of network intrusion detection systems: A novel two phase defense strategy against untargeted white-box optimization adversarial attack
Abstract Machine Learning and Deep Learning based Network Intrusion Detection Systems
(NIDS) serve as the backbone to protect computer networks against various cyber security …
(NIDS) serve as the backbone to protect computer networks against various cyber security …
[HTML][HTML] Comprehensive botnet detection by mitigating adversarial attacks, navigating the subtleties of perturbation distances and fortifying predictions with conformal …
Botnets are computer networks controlled by malicious actors that present significant
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …
Black-box adversarial transferability: An empirical study in cybersecurity perspective
The rapid advancement of artificial intelligence within the realm of cybersecurity raises
significant security concerns. The vulnerability of deep learning models in adversarial …
significant security concerns. The vulnerability of deep learning models in adversarial …
Intelligent In-Network Attack Detection on Programmable Switches with Soterv2
To improve the accuracy of network attack detection, recent work has proposed deep
learning (DL) based detectors. Nonetheless, conventional DL-based solutions are …
learning (DL) based detectors. Nonetheless, conventional DL-based solutions are …
Adaptive Learning in IoT-Based Smart City Applications
Internet of things (IoT) based smart city applications rely on constant data collection and
accurate data analytics, yet the fast-changing nature of such data often causes the …
accurate data analytics, yet the fast-changing nature of such data often causes the …
On the Use of Autoencoders in Unsupervised Learning for Intrusion Detection Systems
LAK Mekemte, G Chalhoub - International Symposium on Ubiquitous …, 2023 - Springer
Cyber attacks are a major threat to countries, large organisations, and small businesses
alike, with serious political, legal, and especially economic consequences. With these cyber …
alike, with serious political, legal, and especially economic consequences. With these cyber …
Adversarial Attacks, Defences and Visualisation for AI-based NIDS
K He - 2024 - researchspace.auckland.ac.nz
Network Intrusion Detection Systems (NIDSes) are crucial in safeguarding computer
networks against malicious activities. Recent NIDS architectures have increasingly adopted …
networks against malicious activities. Recent NIDS architectures have increasingly adopted …
Check for updates On the Use of Autoencoders in Unsupervised Learning for Intrusion Detection Systems
LAK Mekemte, G Chalhoub - … , Clermont-Ferrand, France, November 1–3 … - books.google.com
Cyber attacks are a major threat to countries, large organisations, and small businesses
alike, with serious political, legal, and especially economic consequences. With these cyber …
alike, with serious political, legal, and especially economic consequences. With these cyber …