Matryoshka: Stealing Functionality of Private ML Data by Hiding Models in Model
Authors: Xudong Pan, Yifan Yan, Shengyao Zhang, Mi Zhang, Min Yang | Published: 2022-06-29
Membership Inference
A Framework for Understanding Model Extraction Attack and Defense
Authors: Xun Xian, Mingyi Hong, Jie Ding | Published: 2022-06-23
The Privacy Onion Effect: Memorization is Relative
Authors: Nicholas Carlini, Matthew Jagielski, Chiyuan Zhang, Nicolas Papernot, Andreas Terzis, Florian Tramer | Published: 2022-06-21 | Updated: 2022-06-22
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
Authors: Daryna Oliynyk, Rudolf Mayer, Andreas Rauber | Published: 2022-06-16 | Updated: 2023-06-06
Membership Inference via Backdooring
Authors: Hongsheng Hu, Zoran Salcic, Gillian Dobbie, Jinjun Chen, Lichao Sun, Xuyun Zhang | Published: 2022-06-10
Data Stealing Attack on Medical Images: Is it Safe to Export Networks from Data Lakes?
Authors: Huiyu Li, Nicholas Ayache, Hervé Delingette | Published: 2022-06-07
Subject Membership Inference Attacks in Federated Learning
Authors: Anshuman Suri, Pallika Kanani, Virendra J. Marathe, Daniel W. Peterson | Published: 2022-06-07 | Updated: 2023-06-02
Dropbear: Machine Learning Marketplaces made Trustworthy with Byzantine Model Agreement
Authors: Alex Shamis, Peter Pietzuch, Antoine Delignat-Lavaud, Andrew Paverd, Manuel Costa | Published: 2022-05-31
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning
Authors: Harsh Chaudhari, Matthew Jagielski, Alina Oprea | Published: 2022-05-20 | Updated: 2022-09-08
A False Sense of Security? Revisiting the State of Machine Learning-Based Industrial Intrusion Detection
Authors: Dominik Kus, Eric Wagner, Jan Pennekamp, Konrad Wolsing, Ina Berenice Fink, Markus Dahlmanns, Klaus Wehrle, Martin Henze | Published: 2022-05-18