STRIDE-AI is an ML-specific, asset-centered methodology for identifying threats to AI-based systems.
Below are the reference papers:
L. Mauri and E. Damiani, "STRIDE-AI: An Approach to Identifying Vulnerabilities of Machine Learning Assets," 2021 IEEE International Conference on Cyber Security and Resilience (CSR), 2021, pp. 147-154, doi: 10.1109/CSR51186.2021.9527917.
L. Mauri and E. Damiani, "Modeling Threats to AI-ML Systems Using STRIDE," Sensors. 2022; 22(17):6662. doi: 10.3390/s22176662.
- Failure Mode and Effects Analysis of AI-ML Systems
- ML Assets and their Failure Modes
- Mapping ML Assets' Failure Modes to CIA3-R Hexagon
- Case Study: LIGHT-TOREADOR Platforms
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Lara Mauri1 and Ernesto Damiani1,2
1 Computer Science Department, Università degli Studi di Milano, Milan, Italy
2 Center for Cyber Physical Systems (C2PS), Khalifa University, Abu Dhabi, UAE