Jamie Hayes

Christopher A. Choquette-Choo

Arun Ganesh

Matthew Jagielski

Meenatchi Sundaram Muthu Selva Annamalai

Abhradeep Guha Thakurta

Adam Smith

Andreas Terzis

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Measuring memorization in RLHF for code completion.

[BibT_eX]

[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Scalable watermarking for identifying large language model outputs.

[BibT_eX]

[DOI]

Nat., October, 2024

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice.

[BibT_eX]

[DOI]

CoRR, 2024

To Shuffle or not to Shuffle: Auditing DP-SGD with Shuffling.

[BibT_eX]

[DOI]

CoRR, 2024

Stealing User Prompts from Mixture of Experts.

[BibT_eX]

[DOI]

CoRR, 2024

Measuring memorization through probabilistic discoverable extraction.

[BibT_eX]

[DOI]

CoRR, 2024

UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI.

[BibT_eX]

[DOI]

Ilia Shumailov

Júlio C. S. Jacques Júnior

Eleni Triantafillou

Guillermo Ortiz-Jiménez

CoRR, 2024

Measuring memorization in RLHF for code completion.

[BibT_eX]

[DOI]

CoRR, 2024

Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition.

[BibT_eX]

[DOI]

Gintare Karolina Dziugaite

Peter Triantafillou

Isabelle Guyon

CoRR, 2024

Buffer Overflow in Mixture of Experts.

[BibT_eX]

[DOI]

Ilia Shumailov

Itay Yona

CoRR, 2024

Beyond Slow Signs in High-fidelity Model Extraction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Unlocking Accuracy and Fairness in Differentially Private Image Classification.

[BibT_eX]

[DOI]

CoRR, 2023

Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy.

[BibT_eX]

[DOI]

CoRR, 2023

Differentially Private Diffusion Models Generate Useful Synthetic Images.

[BibT_eX]

[DOI]

CoRR, 2023

Tight Auditing of Differentially Private Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the 32nd USENIX Security Symposium, 2023

Extracting Training Data from Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the 32nd USENIX Security Symposium, 2023

Mnemonist: Locating Model Parameters that Memorize Training Examples.

[BibT_eX]

[DOI]

Ali Shahin Shamsabadi

Adrian Weller

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Towards Unbounded Machine Unlearning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bounding training data reconstruction in DP-SGD.

[BibT_eX]

[DOI]

Saeed Mahloujifar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Webpage Fingerprinting from TLS Traces.

[BibT_eX]

[DOI]

Vasilios Mavroudis

Proceedings of the 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Network, 2023

2022

Unlocking High-Accuracy Differentially Private Image Classification through Scale.

[BibT_eX]

[DOI]

CoRR, 2022

Learning to be adversarially robust and differentially private.

[BibT_eX]

[DOI]

M. Pawan Kumar

CoRR, 2022

Reconstructing Training Data with Informed Adversaries.

[BibT_eX]

[DOI]

Giovanni Cherubin

Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

Local and Central Differential Privacy for Robustness and Privacy in Federated Learning.

[BibT_eX]

[DOI]

Mohammad Naseri

Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

2020

Towards transformation-resilient provenance detection of digital media.

[BibT_eX]

[DOI]

Krishnamurthy Dvijotham

CoRR, 2020

Adaptive Traffic Fingerprinting: Large-scale Inference under Realistic Assumptions.

[BibT_eX]

[DOI]

Vasilios Mavroudis

CoRR, 2020

Toward Robustness and Privacy in Federated Learning: Experimenting with Local and Central Differential Privacy.

[BibT_eX]

[DOI]

Mohammad Naseri

CoRR, 2020

Provable trade-offs between private & robust machine learning.

[BibT_eX]

[DOI]

CoRR, 2020

Unique properties of adversarially trained linear classifiers on Gaussian data.

[BibT_eX]

[DOI]

Krishnamurthy (Dj) Dvijotham

CoRR, 2020

A Framework for robustness Certification of Smoothed Classifiers using F-Divergences.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Extensions and limitations of randomized smoothing for robustness guarantees.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

LOGAN: Membership Inference Attacks Against Generative Models.

[BibT_eX]

[DOI]

Luca Melis

Proc. Priv. Enhancing Technol., 2019

2018

A note on hyperparameters in black-box adversarial examples.

[BibT_eX]

[DOI]

CoRR, 2018

Evading classifiers in discrete domains with provable optimality guarantees.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Universal Adversarial Perturbations with Generative Models.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Security and Privacy Workshops, 2018

Contamination Attacks and Mitigation in Multi-Party Machine Learning.

[BibT_eX]

[DOI]

Olga Ohrimenko

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On Visible Adversarial Perturbations & Digital Watermarking.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

Website Fingerprinting Defenses at the Application Layer.

[BibT_eX]

[DOI]

Giovanni Cherubin

Marc Juarez

Proc. Priv. Enhancing Technol., 2017

Machine Learning as an Adversarial Service: Learning Black-Box Adversarial Examples.

[BibT_eX]

[DOI]

CoRR, 2017

LOGAN: Evaluating Privacy Leakage of Generative Models Using Generative Adversarial Networks.

[BibT_eX]

[DOI]

Luca Melis

CoRR, 2017

ste-GAN-ography: Generating Steganographic Images via Adversarial Training.

[BibT_eX]

[DOI]

CoRR, 2017

AnNotify: A Private Notification Service.

[BibT_eX]

[DOI]

Proceedings of the 2017 on Workshop on Privacy in the Electronic Society, Dallas, TX, USA, October 30, 2017

The Loopix Anonymity System.

[BibT_eX]

[DOI]

Proceedings of the 26th USENIX Security Symposium, 2017

Generating steganographic images via adversarial training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

AnoNotify: A Private Notification Service.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2016

Traffic Confirmation Attacks Despite Noise.

[BibT_eX]

[DOI]

CoRR, 2016

TASP: Towards Anonymity Sets that Persist.

[BibT_eX]

[DOI]

Carmela Troncoso

Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society, 2016

k-fingerprinting: A Robust Scalable Website Fingerprinting Technique.

[BibT_eX]

[DOI]

Proceedings of the 25th USENIX Security Symposium, 2016

2015

Guard Sets for Onion Routing.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2015

Better open-world website fingerprinting.

[BibT_eX]

[DOI]