Reconstructing Training Data with Informed Adversaries

13 January 2022

Papers citing "Reconstructing Training Data with Informed Adversaries"

50 / 111 papers shown

Title
Empirical Privacy Variance Yuzheng Hu Fan Wu Ruicheng Xian Yuhang Liu Lydia Zakynthinou Pritish Kamath Chiyuan Zhang David A. Forsyth 62 0 0 16 Mar 2025
$(\varepsilon, δ)$ Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees Juan Felipe Gomez B. Kulynych G. Kaissis Jamie Hayes Borja Balle Antti Honkela 51 0 0 13 Mar 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 43 0 0 10 Mar 2025
Data Efficient Subset Training with Differential Privacy Ninad Jayesh Gandhi Moparthy Venkata Subrahmanya Sri Harsha 53 0 0 09 Mar 2025
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance Héber H. Arcolezi Sébastien Gambs AAML 48 0 0 03 Mar 2025
SolidMark: Evaluating Image Memorization in Generative Models Nicky Kriplani Minh Pham Gowthami Somepalli Chinmay Hegde Niv Cohen VLM 37 1 0 01 Mar 2025
TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning Weiqi Wang Zhiyi Tian An Liu Shui Yu 72 0 0 27 Feb 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 43 0 0 23 Feb 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 85 0 0 02 Dec 2024
Network Inversion and Its Applications Pirzada Suhail Hao Tang Amit Sethi AAML 63 0 0 26 Nov 2024
Measuring Non-Adversarial Reproduction of Training Data in Large Language Models Michael Aerni Javier Rando Edoardo Debenedetti Nicholas Carlini Daphne Ippolito F. Tramèr 37 3 0 15 Nov 2024
Network Inversion for Training-Like Data Reconstruction Pirzada Suhail Amit Sethi FedML 19 0 0 22 Oct 2024
On the Vulnerability of Text Sanitization Meng Tong Kejiang Chen Xiaojian Yuang J. Liu W. Zhang Nenghai Yu Jie Zhang 52 0 0 22 Oct 2024
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement Zhehao Huang Xinwen Cheng JingHao Zheng Haoran Wang Zhengbao He Tao Li X. Huang MU 40 4 0 29 Sep 2024
Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey Yi Zhang Zhen Chen Chih-Hong Cheng Wenjie Ruan Xiaowei Huang Dezong Zhao David Flynn Siddartha Khastgir Xingyu Zhao MedIm 30 3 0 26 Sep 2024
A Hybrid Quantum Neural Network for Split Learning Hevish Cowlessur Chandra Thapa T. Alpcan S. Çamtepe 16 0 0 25 Sep 2024
Extracting Memorized Training Data via Decomposition Ellen Su Anu Vellore Amy Chang Raffaele Mura Blaine Nelson Paul Kassianik Amin Karbasi 19 2 0 18 Sep 2024
Risks When Sharing LoRA Fine-Tuned Diffusion Model Weights Dixi Yao 17 1 0 13 Sep 2024
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction Attack Chayadon Lumbut Donlapark Ponnoprat 23 0 0 30 Aug 2024
Analyzing Inference Privacy Risks Through Gradients in Machine Learning Zhuohang Li Andrew Lowy Jing Liu T. Koike-Akino K. Parsons Bradley Malin Ye Wang FedML 23 1 0 29 Aug 2024
Attack-Aware Noise Calibration for Differential Privacy B. Kulynych Juan Felipe Gomez G. Kaissis Flavio du Pin Calmon Carmela Troncoso 44 6 0 02 Jul 2024
Towards Efficient and Scalable Training of Differentially Private Deep Learning Sebastian Rodriguez Beltran Marlon Tobaben Niki Loppi Antti Honkela 16 0 0 25 Jun 2024
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy Georgios Kaissis Stefan Kolek Borja Balle Jamie Hayes Daniel Rueckert 40 4 0 13 Jun 2024
Auditing Privacy Mechanisms via Label Inference Attacks R. Busa-Fekete Travis Dick Claudio Gentile Andrés Munoz Medina Adam D. Smith Marika Swanberg 16 0 0 04 Jun 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 19 1 0 01 Jun 2024
Privacy Challenges in Meta-Learning: An Investigation on Model-Agnostic Meta-Learning Mina Rafiei Mohammadmahdi Maheri Hamid R. Rabiee 24 0 0 01 Jun 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable Martín Bertrán Shuai Tang Michael Kearns Jamie Morgenstern Aaron Roth Zhiwei Steven Wu AAML 27 5 0 30 May 2024
Data Reconstruction: When You See It and When You Don't Edith Cohen Haim Kaplan Yishay Mansour Shay Moran Kobbi Nissim Uri Stemmer Eliad Tsfadia AAML 37 2 0 24 May 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model Tudor Cebere A. Bellet Nicolas Papernot 28 9 0 23 May 2024
ATTAXONOMY: Unpacking Differential Privacy Guarantees Against Practical Adversaries Rachel Cummings Shlomi Hod Jayshree Sarathy Marika Swanberg 28 2 0 02 May 2024
VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication Xun Yuan Yang Yang P. Gope A. Pasikhani Biplab Sikdar 21 2 0 15 Apr 2024
MPCPA: Multi-Center Privacy Computing with Predictions Aggregation based on Denoising Diffusion Probabilistic Model Guibo Luo Hanwen Zhang Xiuling Wang Mingzhi Chen Yuesheng Zhu DiffM 26 1 0 12 Mar 2024
Visual Privacy Auditing with Diffusion Models Kristian Schwethelm Johannes Kaiser Moritz Knolle Daniel Rueckert Daniel Rueckert Alexander Ziller DiffM AAML 31 0 0 12 Mar 2024
Fluent: Round-efficient Secure Aggregation for Private Federated Learning Xincheng Li Jianting Ning G. Poh Leo Yu Zhang Xinchun Yin Tianwei Zhang FedML 26 2 0 10 Mar 2024
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training Zihao Wang Rui Zhu Dongruo Zhou Zhikun Zhang John C. Mitchell Haixu Tang XiaoFeng Wang AAML 38 6 0 05 Mar 2024
Differentially Private Representation Learning via Image Captioning Tom Sander Yaodong Yu Maziar Sanjabi Alain Durmus Yi-An Ma Kamalika Chaudhuri Chuan Guo 48 3 0 04 Mar 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks Sayedeh Leila Noorbakhsh Binghui Zhang Yuan Hong Binghui Wang AAML 16 8 0 04 Mar 2024
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach Qi Tan Qi Li Yi Zhao Zhuotao Liu Xiaobing Guo Ke Xu FedML 29 2 0 02 Mar 2024
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy Jamie Hayes Ilia Shumailov Eleni Triantafillou Amr Khalifa Nicolas Papernot MU 33 25 0 02 Mar 2024
Supervised machine learning for microbiomics: bridging the gap between current and best practices Natasha K. Dudek Mariam Chakhvadze Saba Kobakhidze Omar Kantidze Yuriy Gankin LM&MA 27 2 0 27 Feb 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 43 3 0 25 Feb 2024
Bounding Reconstruction Attack Success of Adversaries Without Data Priors Alexander Ziller Anneliese Riess Kristian Schwethelm Tamara T. Mueller Daniel Rueckert Georgios Kaissis MIACV AAML 24 1 0 20 Feb 2024
Measuring Privacy Loss in Distributed Spatio-Temporal Data Tatsuki Koga Casey Meehan Kamalika Chaudhuri 22 0 0 18 Feb 2024
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training Tom Sander Maxime Sylvestre Alain Durmus 23 1 0 13 Feb 2024
Differentially Private Training of Mixture of Experts Models Pierre Tholoniat Huseyin A. Inan Janardhan Kulkarni Robert Sim MoE 19 1 0 11 Feb 2024
Building Guardrails for Large Language Models Yizhen Dong Ronghui Mu Gao Jin Yi Qi Jinwei Hu Xingyu Zhao Jie Meng Wenjie Ruan Xiaowei Huang OffRL 57 27 0 02 Feb 2024
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them Chao-Jung Liu Boxi Chen Wei Shao Chris Zhang Kelvin Wong Yi Zhang 19 3 0 22 Jan 2024
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction) Qiaoyue Tang Frederick Shpilevskiy Mathias Lécuyer 20 13 0 21 Dec 2023
Reconciling AI Performance and Data Reconstruction Resilience for Medical Imaging Alexander Ziller Tamara T. Mueller Simon Stieger Leonhard F. Feiner Johannes Brandt R. Braren Daniel Rueckert Georgios Kaissis 53 1 0 05 Dec 2023
SoK: Memorisation in machine learning Dmitrii Usynin Moritz Knolle Georgios Kaissis 9 1 0 06 Nov 2023