Model extraction from counterfactual explanations
Authors: Ulrich Aïvodji, Alexandre Bolot, Sébastien Gambs | Published: 2020-09-03
Model Extraction Attack
High Accuracy and High Fidelity Extraction of Neural Networks
Authors: Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, Nicolas Papernot | Published: 2019-09-03 | Updated: 2020-03-03
The advantages of multiple classes for reducing overfitting from test set reuse
Authors: Vitaly Feldman, Roy Frostig, Moritz Hardt | Published: 2019-05-24
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
Authors: Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, Yang Zhang | Published: 2019-04-01 | Updated: 2019-11-30
Adversarial Attacks on Time Series
Authors: Fazle Karim, Somshubra Majumdar, Houshang Darabi | Published: 2019-02-27 | Updated: 2019-03-01
Knockoff Nets: Stealing Functionality of Black-Box Models
Authors: Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz | Published: 2018-12-06
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Authors: Milad Nasr, Reza Shokri, Amir Houmansadr | Published: 2018-12-03 | Updated: 2020-06-06
Model-Reuse Attacks on Deep Learning Systems
Authors: Yujie Ji, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang | Published: 2018-12-02
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting
Authors: Clement Fung, Jamie Koerner, Stewart Grant, Ivan Beschastnikh | Published: 2018-11-23 | Updated: 2019-02-24
Exploring Connections Between Active Learning and Model Extraction
Authors: Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan | Published: 2018-11-05 | Updated: 2019-11-20