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Vasisht Duddu
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Journal Articles
- 2020
- [j1]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): 5897-5907 (2020)
Conference and Workshop Papers
- 2023
- [c7]Bailey Kacsmar
, Vasisht Duddu
, Kyle Tilbury
, Blase Ur
, Florian Kerschbaum
:
Comprehension from Chaos: Towards Informed Consent for Private Computation. CCS 2023: 210-224 - 2022
- [c6]Vasisht Duddu, Antoine Boutet:
Inferring Sensitive Attributes from Model Explanations. CIKM 2022: 416-425 - [c5]Vasisht Duddu, Antoine Boutet, Virat Shejwalkar:
Towards privacy aware deep learning for embedded systems. SAC 2022: 520-529 - 2020
- [c4]Vasisht Duddu, D. Vijay Rao:
Quantifying (Hyper) Parameter Leakage in Machine Learning. BigMM 2020: 239-244 - [c3]Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas
:
Towards Enhancing Fault Tolerance in Neural Networks. MobiQuitous 2020: 59-68 - [c2]Vasisht Duddu, Antoine Boutet, Virat Shejwalkar:
Quantifying Privacy Leakage in Graph Embedding. MobiQuitous 2020: 76-85 - 2018
- [c1]Vasisht Duddu, Debasis Samanta, D. Vijay Rao:
Fuzzy Graph Modelling of Anonymous Networks. SOFA (2) 2018: 432-444
Informal and Other Publications
- 2024
- [i17]Anudeep Das, Vasisht Duddu, Rui Zhang, N. Asokan:
Espresso: Robust Concept Filtering in Text-to-Image Models. CoRR abs/2404.19227 (2024) - [i16]Vasisht Duddu, Oskari Järvinen, Lachlan J. Gunn, N. Asokan:
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations. CoRR abs/2406.17548 (2024) - 2023
- [i15]Asim Waheed, Vasisht Duddu, N. Asokan:
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings. CoRR abs/2304.08566 (2023) - [i14]Vasisht Duddu, Anudeep Das, Nora Khayata, Hossein Yalame, Thomas Schneider, N. Asokan:
Attesting Distributional Properties of Training Data for Machine Learning. CoRR abs/2308.09552 (2023) - [i13]Vasisht Duddu, Sebastian Szyller, N. Asokan:
SoK: Unintended Interactions among Machine Learning Defenses and Risks. CoRR abs/2312.04542 (2023) - 2022
- [i12]Vasisht Duddu, Antoine Boutet:
Inferring Sensitive Attributes from Model Explanations. CoRR abs/2208.09967 (2022) - [i11]Bailey Kacsmar, Vasisht Duddu, Kyle Tilbury, Blase Ur, Florian Kerschbaum:
Comprehension from Chaos: What Users Understand and Expect from Private Computation. CoRR abs/2211.07026 (2022) - [i10]Jan Aalmoes, Vasisht Duddu, Antoine Boutet:
Leveraging Algorithmic Fairness to Mitigate Blackbox Attribute Inference Attacks. CoRR abs/2211.10209 (2022) - 2021
- [i9]Sebastian Szyller, Vasisht Duddu, Tommi Gröndahl, N. Asokan:
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks. CoRR abs/2104.12623 (2021) - [i8]Vasisht Duddu, Sebastian Szyller, N. Asokan:
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning. CoRR abs/2112.02230 (2021) - 2020
- [i7]Vasisht Duddu, Antoine Boutet, Virat Shejwalkar:
Quantifying Privacy Leakage in Graph Embedding. CoRR abs/2010.00906 (2020) - [i6]Vasisht Duddu, Antoine Boutet, Virat Shejwalkar:
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning. CoRR abs/2010.00912 (2020) - 2019
- [i5]Vasisht Duddu, D. Vijay Rao, Valentina Emilia Balas:
Adversarial Fault Tolerant Training for Deep Neural Networks. CoRR abs/1907.03103 (2019) - [i4]Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao, Valentina Emilia Balas:
Fault Tolerance of Neural Networks in Adversarial Settings. CoRR abs/1910.13875 (2019) - [i3]Vasisht Duddu, D. Vijay Rao:
Quantifying (Hyper) Parameter Leakage in Machine Learning. CoRR abs/1910.14409 (2019) - 2018
- [i2]Vasisht Duddu, Debasis Samanta:
Network and Security Analysis of Anonymous Communication Networks. CoRR abs/1803.11377 (2018) - [i1]Vasisht Duddu, Debasis Samanta, D. Vijay Rao, Valentina Emilia Balas:
Stealing Neural Networks via Timing Side Channels. CoRR abs/1812.11720 (2018)
Coauthor Index
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