Tag Archives: 2025

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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Feed-Forward Controller-Based Recovery for Robotic Vehicles from Physical Attacks

Pritam Dash, Guanpeng Li, Zitao Chen, Mehdi Karimibiuki, Karthik Pattabiraman. IEEE Transactions on Dependable and Secure Computing (TDSC). [ PDF ]
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DLAFI: Software-Based Fault Injection for Permanent Faults in Deep Learning Accelerators

Seyedmani Sadati, Abraham Chan, Udit Kumar Agarwal and Karthik Pattabiraman. Proceedings of the IEEE International Symposium on Software Reliability Engineering (ISSRE) 2025. (Acceptance Rate: 28%) [ PDF | Talk ] (Code)
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Anonymity Unveiled: A Practical Framework for Auditing Data Use in Deep Learning Models

Zitao Chen and Karthik Pattabiraman, Proceedings of 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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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 ] (Code)
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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 ]. (Code) 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] (Dataset) 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 ] (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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