Evaluating Standard Feature Sets Towards Increased Generalisability and
Explainability of ML-based Network Intrusion Detection

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Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection

15 April 2021

Marius Portmann

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Papers citing "Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-based Network Intrusion Detection"

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Title
Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems Majed Luay S. Layeghy Seyedehfaezeh Hosseininoorbin Mohanad Sarhan Nour Moustafa Marius Portmann 75 1 0 06 Mar 2025
The Cross-evaluation of Machine Learning-based Network Intrusion Detection Systems Giovanni Apruzzese Luca Pajola Mauro Conti 62 55 0 09 Mar 2022
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems Giovanni Apruzzese M. Andreolini Luca Ferretti Mirco Marchetti M. Colajanni AAML 78 108 0 17 Jun 2021
Explaining Network Intrusion Detection System Using Explainable AI Framework Shraddha Mane Dattaraj J. Rao AAML 51 71 0 12 Mar 2021
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 121 6,269 0 22 Oct 2019
Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset Nickolaos Koroniotis Nour Moustafa E. Sitnikova B. Turnbull 56 1,227 0 02 Nov 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 130 1,410 0 08 Dec 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,939 0 22 May 2017