| 2026 | ACL | Locket: Robust Feature-Locking Technique for Language Models. | Lipeng He, Vasisht Duddu, N. Asokan |
| 2026 | EACL | PATCH: Mitigating PII Leakage in Language Models with Privacy-Aware Targeted Circuit PatcHing. | Anthony Hughes, Vasisht Duddu, N. Asokan, Nikolaos Aletras, Ning Ma |
| 2025 | ICML | Position: Contextual Integrity is Inadequately Applied to Language Models. | Yan Shvartzshnaider, Vasisht Duddu |
| 2024 | ESORICS | Attesting Distributional Properties of Training Data for Machine Learning. | Vasisht Duddu, Anudeep Das, Nora Khayata, Hossein Yalame, Thomas Schneider, N. Asokan |
| 2024 | SP | SoK: Unintended Interactions among Machine Learning Defenses and Risks. | Vasisht Duddu, Sebastian Szyller, N. Asokan |
| 2024 | SP | GrOVe: Ownership Verification of Graph Neural Networks using Embeddings. | Asim Waheed, Vasisht Duddu, N. Asokan |
| 2024 | WISE | On the Alignment of Group Fairness with Attribute Privacy. | Jan Aalmoes, Vasisht Duddu, Antoine Boutet |
| 2023 | CCS | Comprehension from Chaos: Towards Informed Consent for Private Computation. | Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum |
| 2022 | CIKM | Inferring Sensitive Attributes from Model Explanations. | Vasisht Duddu, Antoine Boutet |
| 2022 | SAC | Towards privacy aware deep learning for embedded systems. | Vasisht Duddu, Antoine Boutet, Virat Shejwalkar |
| 2020 | Mobiquitous | Quantifying Privacy Leakage in Graph Embedding. | Vasisht Duddu, Antoine Boutet, Virat Shejwalkar |
| 2020 | Mobiquitous | Towards Enhancing Fault Tolerance in Neural Networks. | Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas |
| 2018 | SOFA | Fuzzy Graph Modelling of Anonymous Networks. | Vasisht Duddu, Debasis Samanta, D. Vijay Rao |