Explainable machine learning in cybersecurity: A survey

Author:

Yan Feixue12ORCID,Wen Sheng1,Nepal Surya2,Paris Cecile3,Xiang Yang1

Affiliation:

1. School of Science, Computing and Engineering Technologies Swinburne University of Technology Melbourne Victoria Australia

2. Distributed Systems Security CSIRO's Data61 Sydney New South Wales Australia

3. Knowledge Discovery and Management CSIRO's Data61 Sydney New South Wales Australia

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fair XIDS: Ensuring fairness and transparency in intrusion detection models;Concurrency and Computation: Practice and Experience;2024-08-26

2. Foundations of Cybersecurity;Advances in Information Security, Privacy, and Ethics;2024-08-21

3. Position: The Explainability Paradox - Challenges for XAI in Malware Detection and Analysis;2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW);2024-07-08

4. Advanced insights through systematic analysis: Mapping future research directions and opportunities for xAI in deep learning and artificial intelligence used in cybersecurity;Neurocomputing;2024-07

5. Explainable AI for Cybersecurity;Advances in Computational Intelligence and Robotics;2024-01-18

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