Mohamed Amine Merzouk, Joséphine Delas, Christopher Neal, Frédéric Cuppens
, Nora Boulahia Cuppens and Reda Yaich
Paper (2022)
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| Department: | Department of Computer Engineering and Software Engineering |
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| ISBN: | 9781450396707 |
| PolyPublie URL: | https://publications.polymtl.ca/51405/ |
| Conference Title: | 17th International Conference on Availability, Reliability and Security (ARES 2022) |
| Conference Location: | Vienna, Austria |
| Conference Date(s): | 2022-08-23 - 2022-08-26 |
| Publisher: | Association for Computing Machinery (ACM) |
| DOI: | 10.1145/3538969.3539006 |
| Official URL: | https://doi.org/10.1145/3538969.3539006 |
| Date Deposited: | 18 Apr 2023 14:59 |
| Last Modified: | 08 Apr 2025 14:40 |
| Cite in APA 7: | Merzouk, M. A., Delas, J., Neal, C., Cuppens, F., Boulahia Cuppens, N., & Yaich, R. (2022, August). Evading deep reinforcement learning-based network intrusion detection with adversarial attacks [Paper]. 17th International Conference on Availability, Reliability and Security (ARES 2022), Vienna, Austria (6 pages). https://doi.org/10.1145/3538969.3539006 |
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