Vasisht Duddu
Ph.D. Student, Computer Science
Secure Systems Group
University of Waterloo
vasisht.duddu at uwaterloo.ca
Home Publications Talks Mentoring CV
Legend: Paper Venue Code Miscellaneous Award
2025
- Combining Machine Learning Defenses without Conflicts Paper Code
Vasisht Duddu, Rui Zhang, N. Asokan
Transactions on Machine Learning Research (TMLR) - Investigating Privacy Bias in Training Data of Language Models Paper
Yan Shvartzshnaider, Vasisht Duddu
AAAI Workshop on Privacy-Preserving Artificial Intelligence (AAAI-PPAI) Oral Presentation - Position: Contextual Integrity is Inadequately Applied to Language Models Paper
Yan Shvartzshnaider*, Vasisht Duddu* (equal contribution)
International Conference on Machine Learning (ICML)
- Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations Paper Code Poster@IEEE S&P
Vasisht Duddu, Oskari Järvinen, Lachlan J. Gunn, N. Asokan
ACM Conference on Data and Application Security and Privacy (CODASPY) - Espresso: Robust Concept Filtering in Text-to-Image Models Paper Code
Anudeep Das, Vasisht Duddu, Rui Zhang, N. Asokan
ACM Conference on Data and Application Security and Privacy (CODASPY) Best Paper Award
2024
- SoK: Unintended Interactions among Machine Learning Defenses and Risks Paper Code Blog
Vasisht Duddu, Sebastian Szyller, N. Asokan
IEEE Symposium on Security and Privacy (S&P) Distinguished Paper Award
Industry Impact: Amulet: A Library for Evaluating Interactions among ML Defenses and Risks Code Tech. Transfer to Intel - GrOVe: Ownership Verification of Graph Neural Networks using Embeddings Paper Code
Asim Waheed, Vasisht Duddu, N. Asokan
IEEE Symposium on Security and Privacy (S&P) - Attesting Distributional Properties of Training Data for Machine Learning Paper Code
Vasisht Duddu, Anudeep Das, Nora Khayata, Hossein Yalame, Thomas Schneider, N. Asokan
European Symposium on Research in Computer Security (ESORICS) - On the Alignment of Group Fairness with Attribute Privacy Paper
Jan Aalmoes, Vasisht Duddu, Antoine Boutet
International Web Information Systems Engineering Conference (WISE)
2023
- Comprehension from Chaos: What Users Understand and Expect from Private Computation Paper Code
Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum
ACM Conference on Computer and Communications Security (CCS)
2022
- Inferring Sensitive Attributes from Model Explanations Paper Code
Vasisht Duddu, Antoine Boutet
ACM International Conference on Information and Knowledge Management (CIKM) - Towards Privacy Aware Deep Learning for Embedded Systems Paper Code
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
ACM Symposium On Applied Computing (SAC) NeurIPS Workshop on PPML
2021
- Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation GANs Paper
Sebastian Szyller, Vasisht Duddu, Tommi Gröndahl, N. Asokan
Technical Report
2020
- Quantifying Privacy Leakage in Graph Embedding Paper Code
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous) NeurIPS Workshop on PPML - Fault Tolerance of Neural Networks in Adversarial Settings Paper Code
Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao, Valentina E. Balas
Journal of Intelligent & Fuzzy Systems (JIFS) - Towards Enhancing Fault Tolerance in Neural Networks Paper Code
Vasisht Duddu, D. Vijay Rao, Valentina E. Balas
EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous) - Quantifying (Hyper) Parameter Leakage in Machine Learning Paper Code
Vasisht Duddu, D. Vijay Rao
IEEE International Conference on Multimedia Big Data (BigMM)
2018
- Stealing Neural Networks via Timing Side Channels Paper
Vasisht Duddu, Debasis Samanta, D Vijay Rao, Valentina E. Balas
Technical Report
Theses
- Towards Effective Measurement of Membership Privacy Risk for Machine Learning Models Thesis
Vasisht Duddu
Master's Thesis, University of Waterloo, 2022
Technical Report SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning Paper
Vasisht Duddu, Sebastian Szyller, N. Asokan