Vasisht Duddu
Ph.D. Student, Computer Science
Secure Systems Group
University of Waterloo
vasisht.duddu at uwaterloo.ca



Home Publications Awards Talks Mentoring CV

Pre-Prints

• Locket: Robust Feature-Locking Technique for Language Models Paper Code
  Lipeng He, Vasisht Duddu, N. Asokan
  Under Submission


• PATCH: Mitigating PII Leakage in Language Models with Privacy-Aware Targeted Circuit Patching Paper Code
  Anthony Hughes, Vasisht Duddu, N. Asokan, Nikolaos Aletras, Ning Ma
  Under Submission


• Amulet: A Python Library for Assessing Interactions Among ML Defenses and Risks Paper Code
  Asim Waheed, Vasisht Duddu, Rui Zhang, Sebastian Szyller
  Under Submission Technology Transfer to Intel

2026

• Privacy Bias in Language Models: A Contextual Integrity-based Auditing Metric Paper
  Yan Shvartzshnaider, Vasisht Duddu
  Privacy Enhancing Technologies Symposium (PETS)
  AAAI Workshop on Privacy-Preserving Artificial Intelligence (AAAI-PPAI) Oral Presentation

2025

• Combining Machine Learning Defenses without Conflicts Paper Code
  Vasisht Duddu, Rui Zhang, N. Asokan
  Transactions on Machine Learning Research (TMLR)


• 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: Library for Evaluating Unintended Interactions Code Technology 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