Privacy Backdoors: Stealing Data with Corrupted Pretrained Models

30 March 2024

Papers citing "Privacy Backdoors: Stealing Data with Corrupted Pretrained Models"

18 / 18 papers shown

Title
Behavior Backdoor for Deep Learning Models J. T. Wang Pengfei Zhang R. Tao Jian Yang Hao Liu X. Liu Y. X. Wei Yao Zhao AAML 75 0 0 02 Dec 2024
Backdoored Retrievers for Prompt Injection Attacks on Retrieval Augmented Generation of Large Language Models Cody Clop Yannick Teglia AAML SILM RALM 40 2 0 18 Oct 2024
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage Md. Rafi Ur Rashid Jing Liu T. Koike-Akino Shagufta Mehnaz Ye Wang MU SILM 36 3 0 30 Aug 2024
Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services Shaopeng Fu Xuexue Sun Ke Qing Tianhang Zheng Di Wang AAML MIACV SILM 48 0 0 05 Aug 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
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning Meenatchi Sundaram Muthu Selva Annamalai Emiliano De Cristofaro 28 11 0 23 May 2024
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models Yuxin Wen Leo Marchyok Sanghyun Hong Jonas Geiping Tom Goldstein Nicholas Carlini SILM AAML 26 9 0 01 Apr 2024
PreCurious: How Innocent Pre-Trained Language Models Turn into Privacy Traps Ruixuan Liu Tianhao Wang Yang Cao Li Xiong AAML SILM 45 15 0 14 Mar 2024
Visual Privacy Auditing with Diffusion Models Kristian Schwethelm Johannes Kaiser Moritz Knolle Daniel Rueckert Daniel Rueckert Alexander Ziller DiffM AAML 33 0 0 12 Mar 2024
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering Md. Rafi Ur Rashid Vishnu Asutosh Dasu Kang Gu Najrin Sultana Shagufta Mehnaz AAML FedML 44 10 0 24 Oct 2023
Polynomial Time Cryptanalytic Extraction of Neural Network Models Adi Shamir Isaac Canales-Martínez Anna Hambitzer J. Chávez-Saab Francisco Rodríguez-Henríquez Nitin Satpute AAML MLAU 37 13 0 12 Oct 2023
Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey Victoria Smith Ali Shahin Shamsabadi Carolyn Ashurst Adrian Weller PILM 32 24 0 27 Sep 2023
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 79 92 0 01 Feb 2022
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models Liam H. Fowl Jonas Geiping Steven Reich Yuxin Wen Wojtek Czaja Micah Goldblum Tom Goldstein FedML 71 56 0 29 Jan 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 69 181 0 06 Dec 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 144 349 0 25 Sep 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 267 1,812 0 14 Dec 2020
Cryptanalytic Extraction of Neural Network Models Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 70 134 0 10 Mar 2020