Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification

30 January 2023

Papers citing "Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification"

9 / 9 papers shown

Title
Flow Exporter Impact on Intelligent Intrusion Detection Systems Daniela Pinto João Vitorino Eva Maia Ivone Amorim Isabel Praça 64 1 0 18 Dec 2024
Introducing Perturb-ability Score (PS) to Enhance Robustness Against Problem-Space Evasion Adversarial Attacks on Flow-based ML-NIDS Mohamed elShehaby Ashraf Matrawy AAML 19 0 0 11 Sep 2024
Efficient Network Traffic Feature Sets for IoT Intrusion Detection Miguel Silva João Vitorino Eva Maia Isabel Praça 19 0 0 12 Jun 2024
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection João Vitorino Miguel Silva Eva Maia Isabel Praça AAML 22 6 0 05 Apr 2024
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection João Vitorino Miguel Silva Eva Maia Isabel Praça AAML 21 4 0 25 Feb 2024
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection Kahraman Kostas Mike Just M. Lones 15 6 0 17 Oct 2023
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection João Vitorino Isabel Praça Eva Maia AAML 15 22 0 13 Aug 2023
Adversarial Robustness and Feature Impact Analysis for Driver Drowsiness Detection João Vitorino Lourencco Rodrigues Eva Maia Isabel Praça André Lourencco AAML 8 0 0 23 Mar 2023
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 175 271 0 03 Dec 2018