Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan, To appear in the Proceedings of the ACM International Symposium on Applied Computing (SAC), 2025. Safe, Secure, and Robust AI Track. (Acceptance Rate: TBD) [ PDF | Talk ] (code)
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Recent Papers
- D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles
- A Method to Facilitate Membership Inference Attacks in Deep Learning Models
- SAM: Foreseeing Inference-Time False Data Injection Attacks on ML-enabled Medical Devices
- AutoPatch: Automated Generation of Hotpatches for Real-Time Embedded Devices
- SpecGuard: Specification Aware Recovery for Robotic Autonomous Vehicles from Physical Attacks
- Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models
- Co-Approximator: Enabling Performance Prediction in Colocated Applications
- Harnessing Explainability to Improve ML Ensemble Resilience
- POMABuster: Detecting Price Oracle Manipulation Attacks in Decentralized Finance
- Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems
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