Vasisht Duddu

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Sensitive Attributes

Graph Embedding

Top Venues

Publications

Anudeep Das, Vasisht Duddu, Rui Zhang, N. Asokan
Espresso: Robust Concept Filtering in Text-to-Image Models. CoRR (2024)
Vasisht Duddu, Oskari Järvinen, Lachlan J. Gunn, N. Asokan
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations. CoRR (2024)
Vasisht Duddu, Sebastian Szyller, N. Asokan
SoK: Unintended Interactions among Machine Learning Defenses and Risks. CoRR (2023)
Asim Waheed, Vasisht Duddu, N. Asokan
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings. CoRR (2023)
Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum
Comprehension from Chaos: Towards Informed Consent for Private Computation. CCS (2023)
Vasisht Duddu, Anudeep Das, Nora Khayata, Hossein Yalame, Thomas Schneider, N. Asokan
Attesting Distributional Properties of Training Data for Machine Learning. CoRR (2023)
Jan Aalmoes, Vasisht Duddu, Antoine Boutet
Leveraging Algorithmic Fairness to Mitigate Blackbox Attribute Inference Attacks. CoRR (2022)
Jan Aalmoes, Vasisht Duddu, Antoine Boutet
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks. CoRR (2022)
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
Towards privacy aware deep learning for embedded systems. SAC (2022)
Vasisht Duddu, Antoine Boutet
Inferring Sensitive Attributes from Model Explanations. CoRR (2022)
Vasisht Duddu, Antoine Boutet
Inferring Sensitive Attributes from Model Explanations. CIKM (2022)
Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum
Comprehension from Chaos: What Users Understand and Expect from Private Computation. CoRR (2022)
Sebastian Szyller, Vasisht Duddu, Tommi Gröndahl, N. Asokan
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks. CoRR (2021)
Vasisht Duddu, Sebastian Szyller, N. Asokan
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning. CoRR (2021)
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
Quantifying Privacy Leakage in Graph Embedding. CoRR (2020)
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning. CoRR (2020)
Vasisht Duddu, D. Vijay Rao
Quantifying (Hyper) Parameter Leakage in Machine Learning. BigMM (2020)
Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao, Valentina Emilia Balas
Fault tolerance of neural networks in adversarial settings. J. Intell. Fuzzy Syst. 38 (5) (2020)
Vasisht Duddu, Antoine Boutet, Virat Shejwalkar
Quantifying Privacy Leakage in Graph Embedding. MobiQuitous (2020)
Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas
Towards Enhancing Fault Tolerance in Neural Networks. MobiQuitous (2020)
Vasisht Duddu, D. Vijay Rao
Quantifying (Hyper) Parameter Leakage in Machine Learning. CoRR (2019)
Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao, Valentina Emilia Balas
Fault Tolerance of Neural Networks in Adversarial Settings. CoRR (2019)
Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas
Adversarial Fault Tolerant Training for Deep Neural Networks. CoRR (2019)
Vasisht Duddu, Debasis Samanta
Network and Security Analysis of Anonymous Communication Networks. CoRR (2018)
Vasisht Duddu, Debasis Samanta, D. Vijay Rao, Valentina Emilia Balas
Stealing Neural Networks via Timing Side Channels. CoRR (2018)
Vasisht Duddu, Debasis Samanta, D. Vijay Rao
Fuzzy Graph Modelling of Anonymous Networks. SOFA (2) (2018)