Towards Query Efficient Black-box Attacks: An Input-free Perspective
Authors: Yali Du, Meng Fang, Jinfeng Yi, Jun Cheng, Dacheng Tao | Published: 2018-09-09
ポイズニング
Adversarial Attacks on Node Embeddings via Graph Poisoning
Authors: Aleksandar Bojchevski, Stephan Günnemann | Published: 2018-09-04 | Updated: 2019-05-27
Mitigating Sybils in Federated Learning Poisoning
Authors: Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh | Published: 2018-08-14 | Updated: 2020-07-15
Gradient Band-based Adversarial Training for Generalized Attack Immunity of A3C Path Finding
Authors: Tong Chen, Wenjia Niu, Yingxiao Xiang, Xiaoxuan Bai, Jiqiang Liu, Zhen Han, Gang Li | Published: 2018-07-18
Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data
Authors: Jacson Rodrigues Correia-Silva, Rodrigo F. Berriel, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos | Published: 2018-06-14
Adversarial Regression with Multiple Learners
Authors: Liang Tong, Sixie Yu, Scott Alfeld, Yevgeniy Vorobeychik | Published: 2018-06-06
Adversarial Attacks on Neural Networks for Graph Data
Authors: Daniel Zügner, Amir Akbarnejad, Stephan Günnemann | Published: 2018-05-21 | Updated: 2021-12-09
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
Authors: Tribhuvanesh Orekondy, Seong Joon Oh, Yang Zhang, Bernt Schiele, Mario Fritz | Published: 2018-05-15 | Updated: 2020-09-13
Is feature selection secure against training data poisoning?
Authors: Huang Xiao, Battista Biggio, Gavin Brown, Giorgio Fumera, Claudia Eckert, Fabio Roli | Published: 2018-04-21
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
Authors: Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, Tom Goldstein | Published: 2018-04-03 | Updated: 2018-11-10