Vasisht Duddu

According to our database, Vasisht Duddu authored at least 23 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

LLM-CI: Assessing Contextual Integrity Norms in Language Models.

Yan Shvartzshnaider, Vasisht Duddu, John Lacalamita

CoRR, 2024

Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations.

Vasisht Duddu, Oskari Järvinen, Lachlan J. Gunn, N. Asokan

CoRR, 2024

Espresso: Robust Concept Filtering in Text-to-Image Models.

Anudeep Das, Vasisht Duddu, Rui Zhang, N. Asokan

CoRR, 2024

On the Alignment of Group Fairness with Attribute Privacy.

Jan Aalmoes, Vasisht Duddu, Antoine Boutet

Proceedings of the Web Information Systems Engineering - WISE 2024, 2024

GrOVe: Ownership Verification of Graph Neural Networks using Embeddings.

Asim Waheed, Vasisht Duddu, N. Asokan

Proceedings of the IEEE Symposium on Security and Privacy, 2024

SoK: Unintended Interactions among Machine Learning Defenses and Risks.

Vasisht Duddu, Sebastian Szyller, N. Asokan

Proceedings of the IEEE Symposium on Security and Privacy, 2024

Attesting Distributional Properties of Training Data for Machine Learning.

Vasisht Duddu, Anudeep Das, Nora Khayata, Hossein Yalame, Thomas Schneider, N. Asokan

Proceedings of the Computer Security - ESORICS 2024, 2024

2023

Comprehension from Chaos: Towards Informed Consent for Private Computation.

Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

Leveraging Algorithmic Fairness to Mitigate Blackbox Attribute Inference Attacks.

Jan Aalmoes, Vasisht Duddu, Antoine Boutet

CoRR, 2022

Comprehension from Chaos: What Users Understand and Expect from Private Computation.

Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum

CoRR, 2022

Towards privacy aware deep learning for embedded systems.

Vasisht Duddu, Antoine Boutet, Virat Shejwalkar

Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Inferring Sensitive Attributes from Model Explanations.

Vasisht Duddu, Antoine Boutet

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning.

Vasisht Duddu, Sebastian Szyller, N. Asokan

CoRR, 2021

Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks.

Sebastian Szyller, Vasisht Duddu, Tommi Gröndahl, N. Asokan

CoRR, 2021

2020

Fault tolerance of neural networks in adversarial settings.

Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao, Valentina Emilia Balas

J. Intell. Fuzzy Syst., 2020

GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning.

Vasisht Duddu, Antoine Boutet, Virat Shejwalkar

CoRR, 2020

Towards Enhancing Fault Tolerance in Neural Networks.

Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas

Proceedings of the MobiQuitous '20: Computing, 2020

Quantifying Privacy Leakage in Graph Embedding.

Vasisht Duddu, Antoine Boutet, Virat Shejwalkar

Proceedings of the MobiQuitous '20: Computing, 2020

Quantifying (Hyper) Parameter Leakage in Machine Learning.

Vasisht Duddu, D. Vijay Rao

Proceedings of the 6th IEEE International Conference on Multimedia Big Data, 2020

2019

Adversarial Fault Tolerant Training for Deep Neural Networks.

Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas

CoRR, 2019

2018

Stealing Neural Networks via Timing Side Channels.

Vasisht Duddu, Debasis Samanta, D. Vijay Rao, Valentina Emilia Balas

CoRR, 2018

Network and Security Analysis of Anonymous Communication Networks.

Vasisht Duddu, Debasis Samanta

CoRR, 2018

Fuzzy Graph Modelling of Anonymous Networks.

Vasisht Duddu, Debasis Samanta, D. Vijay Rao

Proceedings of the Soft Computing Applications, 2018