Tag Archives: ML

Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices

Gargi Mitra, Mohammadreza Hallajiyan, Inji Kim, Athish Pranav Dharmalingam, Mohammed ElNawawy, Sharear Iqbal, Karthik Pattabiraman, Homa Alemzadeh. Springer Nature, 2026. (Invited) (arXIV version)
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Anonymity Unveiled: A Practical Framework for Auditing Data Use in Deep Learning Models

Zitao Chen and Karthik Pattabiraman, To appear in the ACM Conference on Computer and Communications Security (CCS), 2025. (Acceptance Rate: 14.5%) [ PDF | Talk ] (Code) Artifacts Available, Functional and Results Reproduced

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ReMlX: Resilience for ML Ensembles using XAI at Inference against Faulty Training Data

Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan. Proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2025. (Acceptance Rate: 20.1%) [ PDF | Talk ] (Code) Artifacts available, reviewed and reproducible.
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D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles

Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan, Proceedings of the ACM International Symposium on Applied Computing (SAC), 2025. Safe, Secure, and Robust AI Track. (Acceptance Rate: 23%) [ PDF | Talk ] (code)
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A Method to Facilitate Membership Inference Attacks in Deep Learning Models

Zitao Chen and Karthik Pattabiraman, Proceedings of the ISOC Network and Distributed Systems Security Symposium (NDSS), 2025. (Acceptance Rate: 16.1%) [ PDF | Talk ] (Code) (arXIV version). Artifacts Available, Functional and Results Reproduced.
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Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models

Qutub Syed, Michael Paulitsch, Karthik Pattabiraman, Korbinian Hagn1, Fabian Oboril, Cornelius Buerkle, Kay-Ulrich Scholl, Gereon Hinz and Alois Knoll, Proceedings of the IJCAI-AISafety Workshop, 2024. [ PDF | Talk ]
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Harnessing Explainability to Improve ML Ensemble Resilience

Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan, Supplementary proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2024. Disrupt Track. (Acceptance Rate: TBD) [ PDF | Talk ]
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Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction

Zitao Chen and Karthik Pattabiraman, Proceedings of the Network and Distributed Systems Security Conference (NDSS), 2024. (Acceptance Rate: 15%). [ PDF | Talk ] (ArXIV, Code). Artifacts Available, Functional and Reproduced
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Evaluating the Effect of Common Annotation Faults on Object Detection Techniques

Abraham Chan, Arpan Gujarati, Karthik Pattabiraman and Sathish Gopalakrishnan, Proceedings of the IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023. (Acceptance Rate: 28.5%) [ PDF | Talk ] (Code). Artifacts Available and Reviewed.

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Resilience Assessment of Large Language Models under Transient Hardware Faults

Udit Agarwal, Abraham Chan, and Karthik Pattabiraman, Proceedings of the IEEE International Symposium on Software Reliability Engineering (ISSRE), 2023. (Acceptance Rate: 28.5%) [ PDF | Talk ] (Code). Artifacts Available and Reviewed.
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