Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets

31 March 2022

Sanghyun Hong

Papers citing "Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets"

32 / 82 papers shown

Title
A Generative Framework for Low-Cost Result Validation of Machine Learning-as-a-Service Inference Abhinav Kumar Miguel A. Guirao Aguilera R. Tourani S. Misra AAML 21 0 0 31 Mar 2023
Do Backdoors Assist Membership Inference Attacks? Yumeki Goto Nami Ashizawa Toshiki Shibahara Naoto Yanai MIACV 17 2 0 22 Mar 2023
Secret-Keeping in Question Answering Nathaniel W. Rollings Kent O'Sullivan Sakshum Kulshrestha KELM 30 0 0 16 Mar 2023
Students Parrot Their Teachers: Membership Inference on Model Distillation Matthew Jagielski Milad Nasr Christopher A. Choquette-Choo Katherine Lee Nicholas Carlini FedML 41 21 0 06 Mar 2023
Poisoning Web-Scale Training Datasets is Practical Nicholas Carlini Matthew Jagielski Christopher A. Choquette-Choo Daniel Paleka Will Pearce Hyrum S. Anderson Andreas Terzis Kurt Thomas Florian Tramèr SILM 31 182 0 20 Feb 2023
Membership Inference Attacks against Diffusion Models Tomoya Matsumoto Takayuki Miura Naoto Yanai DiffM 25 53 0 07 Feb 2023
Uncovering Adversarial Risks of Test-Time Adaptation Tong Wu Feiran Jia Xiangyu Qi Jiachen T. Wang Vikash Sehwag Saeed Mahloujifar Prateek Mittal AAML TTA 29 9 0 29 Jan 2023
SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning A. Salem Giovanni Cherubin David E. Evans Boris Köpf Andrew J. Paverd Anshuman Suri Shruti Tople Santiago Zanella Béguelin 44 35 0 21 Dec 2022
Membership Inference Attacks Against Semantic Segmentation Models Tomás Chobola Dmitrii Usynin Georgios Kaissis MIACV 24 6 0 02 Dec 2022
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis Lukas Struppek Dominik Hintersdorf Kristian Kersting SILM 22 36 0 04 Nov 2022
Amplifying Membership Exposure via Data Poisoning Yufei Chen Chao Shen Yun Shen Cong Wang Yang Zhang AAML 43 27 0 01 Nov 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 29 2 0 28 Oct 2022
Efficient Privacy-Preserving Machine Learning with Lightweight Trusted Hardware Pengzhi Huang Thang Hoang Yueying Li Elaine Shi G. E. Suh 17 2 0 18 Oct 2022
Data Isotopes for Data Provenance in DNNs Emily Wenger Xiuyu Li Ben Y. Zhao Vitaly Shmatikov 20 12 0 29 Aug 2022
SNAP: Efficient Extraction of Private Properties with Poisoning Harsh Chaudhari John Abascal Alina Oprea Matthew Jagielski Florian Tramèr Jonathan R. Ullman MIACV 34 30 0 25 Aug 2022
Verifiable Encodings for Secure Homomorphic Analytics Sylvain Chatel Christian Knabenhans Apostolos Pyrgelis Carmela Troncoso Jean-Pierre Hubaux 23 19 0 28 Jul 2022
Combing for Credentials: Active Pattern Extraction from Smart Reply Bargav Jayaraman Esha Ghosh Melissa Chase Sambuddha Roy Wei Dai David E. Evans SILM 20 8 0 14 Jul 2022
Conflicting Interactions Among Protection Mechanisms for Machine Learning Models S. Szyller Nadarajah Asokan AAML 26 7 0 05 Jul 2022
Measuring Forgetting of Memorized Training Examples Matthew Jagielski Om Thakkar Florian Tramèr Daphne Ippolito Katherine Lee ... Eric Wallace Shuang Song Abhradeep Thakurta Nicolas Papernot Chiyuan Zhang TDI 50 102 0 30 Jun 2022
The Privacy Onion Effect: Memorization is Relative Nicholas Carlini Matthew Jagielski Chiyuan Zhang Nicolas Papernot Andreas Terzis Florian Tramèr PILM MIACV 33 99 0 21 Jun 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 11 17 0 06 Jun 2022
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning Harsh Chaudhari Matthew Jagielski Alina Oprea 28 7 0 20 May 2022
On the (In)security of Peer-to-Peer Decentralized Machine Learning Dario Pasquini Mathilde Raynal Carmela Troncoso OOD FedML 35 19 0 17 May 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 81 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
Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models Shagufta Mehnaz S. V. Dibbo Ehsanul Kabir Ninghui Li E. Bertino MIACV 37 60 0 23 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
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 19 231 0 18 Nov 2021
Unadversarial Examples: Designing Objects for Robust Vision Hadi Salman Andrew Ilyas Logan Engstrom Sai H. Vemprala A. Madry Ashish Kapoor WIGM 62 59 0 22 Dec 2020
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 290 1,814 0 14 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 179 1,032 0 29 Nov 2018
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016