SAD-GAN: A Novel Secure Anomaly Detection Framework for Enhancing the Resilience of Cyber-Physical Systems
(2025)
Journal Article
Bhutani, M., Dalal, S., Alhussein, M., Lilhore, U. K., Aurangzeb, K., & Hussain, A. (2025). SAD-GAN: A Novel Secure Anomaly Detection Framework for Enhancing the Resilience of Cyber-Physical Systems. Cognitive Computation, 17(4), Article 127. https://doi.org/10.1007/s12559-025-10483-5
Cyber-physical systems occupy a significant portion of the critical infrastructure market, but their prominence has raised concerns due to their susceptibility to certain anomalies. The typical approaches tend to be ineffective to flexible and comple... Read More about SAD-GAN: A Novel Secure Anomaly Detection Framework for Enhancing the Resilience of Cyber-Physical Systems.