Tag Archives: 2025

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: TBD) [ PDF (coming soon) | Talk ]

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OneOS: Distributed Operating System for the Edge-to-Cloud Continuum

Kumseok Jung, Julien Gascon Samson, Sathish Gopalakrishnan, and Karthik Pattabiraman, IEEE Transactions on Parallel and Distributed Systems (TPDS). [ PDF ]
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RAVAGE: Robotic Autonomous Vehicles’ Attack Generation Engine

Pritam Dash and Karthik Pattabiraman, Proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2025. (Acceptance Rate: 20.1%) [ PDF | Talk ]. Artifacts available, reviewed and reproducible.
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Reentrancy Redux: The Evolution of Real-World Reentrancy Attacks on Blockchains

Yuqi Liu, Rui Xi, and Karthik Pattabiraman, Proceedings of the IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2025. (Acceptance Rate: 20.1%). [ PDF | Talk] Artifacts available, reviewed and reproducible.
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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 ] 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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