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Jamie Hayes
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LOGAN: evaluating privacy leakage of generative models using generative adversarial networks
J Hayes, L Melis, G Danezis, E De Cristofaro
arXiv preprint arXiv:1705.07663, 506-519, 2017
437*2017
k-fingerprinting: A Robust Scalable Website Fingerprinting Technique.
J Hayes, G Danezis
USENIX security symposium, 1187-1203, 2016
3152016
Generating steganographic images via adversarial training
J Hayes, G Danezis
Advances in neural information processing systems 30, 2017
2212017
The loopix anonymity system
AM Piotrowska, J Hayes, T Elahi, S Meiser, G Danezis
26th {USENIX} Security Symposium ({USENIX} Security 17), 1199-1216, 2017
1672017
Learning universal adversarial perturbations with generative models
J Hayes, G Danezis
2018 IEEE Security and Privacy Workshops (SPW), 43-49, 2018
1102018
Website Fingerprinting Defenses at the Application Layer.
G Cherubin, J Hayes, M Juarez
Proc. Priv. Enhancing Technol. 2017 (2), 186-203, 2017
742017
Contamination attacks and mitigation in multi-party machine learning
J Hayes, O Ohrimenko
Advances in neural information processing systems 31, 2018
722018
On visible adversarial perturbations & digital watermarking
J Hayes
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
682018
Toward robustness and privacy in federated learning: Experimenting with local and central differential privacy
M Naseri, J Hayes, E De Cristofaro
arXiv preprint arXiv:2009.03561, 2020
542020
Guard Sets for Onion Routing
J Hayes, G Danezis
Proceedings on Privacy Enhancing Technologies 1 (2), Pages 65–80, 2015
34*2015
A framework for robustness certification of smoothed classifiers using f-divergences
KD Dvijotham, J Hayes, B Balle, Z Kolter, C Qin, A Gyorgy, K Xiao, ...
322020
Local and central differential privacy for robustness and privacy in federated learning
M Naseri, J Hayes, E De Cristofaro
arXiv preprint arXiv:2009.03561, 2020
302020
Unlocking high-accuracy differentially private image classification through scale
S De, L Berrada, J Hayes, SL Smith, B Balle
arXiv preprint arXiv:2204.13650, 2022
262022
Evading classifiers in discrete domains with provable optimality guarantees
B Kulynych, J Hayes, N Samarin, C Troncoso
arXiv preprint arXiv:1810.10939, 2018
202018
AnNotify: A private notification service
AM Piotrowska, J Hayes, N Gelernter, G Danezis, A Herzberg
Proceedings of the 2017 on Workshop on Privacy in the Electronic Society, 5-15, 2017
192017
Extensions and limitations of randomized smoothing for robustness guarantees
J Hayes
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
172020
Reconstructing training data with informed adversaries
B Balle, G Cherubin, J Hayes
2022 IEEE Symposium on Security and Privacy (SP), 1138-1156, 2022
162022
TASP: Towards anonymity sets that persist
J Hayes, C Troncoso, G Danezis
Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society …, 2016
62016
Traffic confirmation attacks despite noise
J Hayes
arXiv preprint arXiv:1601.04893, 2016
62016
Provable trade-offs between private & robust machine learning
J Hayes
arXiv preprint arXiv:2006.04622, 2020
52020
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Articles 1–20