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virat shejwalkar
virat shejwalkar
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Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning
V Shejwalkar, A Houmansadr
Network and Distributed System Security Symposium, NDSS, 2021
2772021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning
V Shejwalkar, A Houmansadr, P Kairouz, D Ramage
IEEE Symposium on Security and Privacy, 2022
2012022
Cronus: Robust and heterogeneous collaborative learning with black-box knowledge transfer
H Chang, V Shejwalkar, R Shokri, A Houmansadr
NeurIPS Workshop on New Frontiers in Federated Learning, 2021
1552021
Quantifying Privacy Leakage in Graph Embedding
V Duddu, A Boutet, V Shejwalkar
EAI MobiQuitous, 2021
992021
Membership Privacy for Machine Learning Models Through Knowledge Transfer
V Shejwalkar, A Houmansadr
AAAI, 2021
872021
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
X Tang, S Mahloujifar, L Song, V Shejwalkar, M Nasr, A Houmansadr, ...
USENIX Security Symposium, 2022
602022
Membership inference attacks against nlp classification models
V Shejwalkar, HA Inan, A Houmansadr, R Sim
NeurIPS 2021 Workshop Privacy in Machine Learning, 2021
402021
FRL: Federated Rank Learning
H Mozaffari, V Shejwalkar, A Houmansadr
USENIX Security Symposium, 2023
17*2023
Reconciling utility and membership privacy via knowledge distillation
V Shejwalkar, A Houmansadr
arXiv e-prints, arXiv: 1906.06589, 2019
152019
Machine Learning with Differentially Private Labels: Mechanisms and Frameworks
X Tang, M Nasr, S Mahloujifar, V Shejwalkar, L Song, A Houmansadr, ...
Proceedings on Privacy Enhancing Technologies 1, 19, 2022
102022
Towards privacy aware deep learning for embedded systems
V Duddu, A Boutet, V Shejwalkar
Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, 520-529, 2022
9*2022
The perils of learning from unlabeled data: Backdoor attacks on semi-supervised learning
V Shejwalkar, L Lyu, A Houmansadr
International Conference on Computer Vision (ICCV), 2023
82023
Security analysis of splitfed learning
MA Khan, V Shejwalkar, A Houmansadr, FM Anwar
Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems …, 2022
72022
Recycling scraps: Improving private learning by leveraging intermediate checkpoints
V Shejwalkar, A Ganesh, R Mathews, O Thakkar, A Thakurta
arXiv preprint arXiv:2210.01864, 2022
62022
Cronus: Robust and heterogeneous collaborative learning with black-box knowledge transfer
C Hongyan, S Virat, S Reza, H Amir
arXiv preprint arXiv:1912.11279, 2019
52019
Leveraging prior knowledge asymmetries in the design of location privacy-preserving mechanisms
N Takbiri, V Shejwalkar, A Houmansadr, DL Goeckel, H Pishro-Nik
IEEE Wireless Communications Letters 9 (11), 2005-2009, 2020
32020
On the pitfalls of security evaluation of robust federated learning
MA Khan, V Shejwalkar, A Houmansadr, FM Anwar
2023 IEEE Security and Privacy Workshops (SPW), 57-68, 2023
22023
Quantifying and Enhancing the Security of Federated Learning
VV Shejwalkar
12023
Revisiting utility metrics for location privacy-preserving mechanisms
V Shejwalkar, A Houmansadr, H Pishro-Nik, D Goeckel
Proceedings of the 35th Annual Computer Security Applications Conference …, 2019
12019
Leveraging intermediate checkpoints to improve the performance of trained differentially private models
OD Thakkar, A Ganesh, VV Shejwalkar, AG Thakurta, R Mathews
US Patent App. 18/459,354, 2024
2024
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