| Stealing Neural Networks via Timing Side Channels V Duddu, D Samanta, DV Rao, VE Balas Technical Report, 2018 | 162 | 2018 |
| Quantifying Privacy Leakage in Graph Embedding V Duddu, A Boutet, V Shejwalkar International Conference on Mobile and Ubiquitous Systems (MobiQuitous), 2020 | 129 | 2020 |
| On the Alignment of Group Fairness with Attribute Privacy J Aalmoes, V Duddu, A Boutet International Web Information Systems Engineering Conference (WISE), 2024 | 18* | 2024 |
| Inferring Sensitive Attributes from Model Explanations V Duddu, A Boutet ACM Conference on Information and Knowledge Management (CIKM), 2022 | 18 | 2022 |
| Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models S Szyller, V Duddu, T Gröndahl, N Asokan Technical Report, 2021 | 18* | 2021 |
| Fault Tolerance of Neural Networks in Adversarial Settings V Duddu, N Rajesh Pillai, DV Rao, VE Balas Journal of Intelligent & Fuzzy Systems (JIFS), 2020 | 15 | 2020 |
| Towards Effective Measurement of Membership Privacy Risk for Machine Learning Models V Duddu Master's Thesis @ University of Waterloo, 2022 | 13* | 2022 |
| Towards Enhancing Fault Tolerance in Neural Networks V Duddu, DV Rao, VE Balas International Conference on Mobile and Ubiquitous Systems (MobiQuitous), 2020 | 12* | 2020 |
| Towards privacy aware deep learning for embedded systems V Duddu, A Boutet, V Shejwalkar ACM Symposium on Applied Computing (SAC), 2022 | 10* | 2022 |
| Quantifying (hyper) parameter leakage in machine learning V Duddu, DV Rao IEEE Sixth International Conference on Multimedia Big Data (BigMM), 239-244, 2020 | 7 | 2020 |
| Comprehension from Chaos: What Users Understand and Expect from Private Computation B Kacsmar, V Duddu, K Tilbury, B Ur, F Kerschbaum ACM Conference on Computer and Communications Security (CCS), 2023 | 5* | 2023 |
| Attesting distributional properties of training data for machine learning V Duddu, A Das, N Khayata, H Yalame, T Schneider, N Asokan European Symposium on Research in Computer Security (ESORICS), 2024 | 4 | 2024 |
| GrOVe: Ownership Verification of Graph Neural Networks using Embeddings A Waheed, V Duddu, N Asokan IEEE Symposium on Security and Privacy (S&P), 2024 | 4 | 2024 |
| Llm-ci: Assessing contextual integrity norms in language models Y Shvartzshnaider, V Duddu, J Lacalamita arXiv preprint arXiv:2409.03735, 2024 | 3 | 2024 |
| Espresso: Robust Concept Filtering in Text-to-Image Models A Das, V Duddu, R Zhang, N Asokan arXiv preprint arXiv:2404.19227, 2024 | 3 | 2024 |
| SoK: Unintended Interactions among Machine Learning Defenses and Risks V Duddu, S Szyller, N Asokan 🏆 IEEE Symposium on Security and Privacy (S&P) [Distinguished Paper Award], 2024 | 3 | 2024 |
| Combining Machine Learning Defenses without Conflicts V Duddu, R Zhang, N Asokan arXiv preprint arXiv:2411.09776, 2024 | | 2024 |
| Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations V Duddu, O Järvinen, LJ Gunn, N Asokan arXiv preprint arXiv:2406.17548, 2024 | | 2024 |
antoine boutetAssistant Professor, INSA-Lyon, CITI / Privatics InriaVerified email at insa-lyon.fr
