Robust Intrusion Detection With Combinatorial Fusion and Generative Artificial Intelligence
This article proposes an advanced intrusion detection system that combines combinatorial fusion analysis with generative artificial intelligence to improve anomaly detection in intelligent systems. It addresses challenges in detecting low-profile and evolving threats, especially in imbalanced datasets.
Authors
- Mohamed Rahouti (ORCID: https://orcid.org/0000-0001-9701-5505)
- Evans Owusu (ORCID: https://orcid.org/0000-0003-0772-3271)
- Dinesh Verma (ORCID: https://orcid.org/0000-0003-1933-7343)
- Mariyam Mapkar
Institutions
- Fordham University (US)
- IBM Research - Thomas J. Watson Research Center (US)
Publication Details
- Journal
- Computer
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1109/mc.2024.3524302
- Citations
- 3
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 4.46