Adversarial Machine Learning in Network Intrusion Detection Systems

23 April 2020

Papers citing "Adversarial Machine Learning in Network Intrusion Detection Systems"

8 / 8 papers shown

Title
Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability Anass Grini Oumaima Taheri Btissam El Khamlichi Amal El Fallah-Seghrouchni AAML 49 0 0 02 May 2025
Evaluating The Explainability of State-of-the-Art Deep Learning-based Network Intrusion Detection Systems Ayush Kumar V. Thing 65 0 0 21 Feb 2025
Manipulating hidden-Markov-model inferences by corrupting batch data William N. Caballero Jose Manuel Camacho Tahir Ekin Roi Naveiro AAML 30 1 0 19 Feb 2024
A Novel Deep Learning based Model to Defend Network Intrusion Detection System against Adversarial Attacks Khushnaseeb Roshan Aasim Zafar Shiekh Burhan Ul Haque AAML 10 8 0 31 Jul 2023
Adversarial Learning in Real-World Fraud Detection: Challenges and Perspectives Daniele Lunghi A. Simitsis O. Caelen Gianluca Bontempi AAML FaML 48 4 0 03 Jul 2023
Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation Soumyadeep Hore Jalal Ghadermazi Diwas Paudel Ankit Shah Tapas K. Das Nathaniel D. Bastian AAML 24 13 0 18 May 2023
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System Zongming Lin Thomas Pike Mark M. Bailey Nathaniel D. Bastian OOD 21 2 0 08 Nov 2022
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 39 105 0 17 Jun 2021