FGAN: Federated Generative Adversarial Networks for Anomaly Detection in Network Traffic
Authors: Sankha Das | Published: 2022-03-21
生成的敵対ネットワーク
Learning Image Attacks toward Vision Guided Autonomous Vehicles
Authors: Hyung-Jin Yoon, Hamidreza Jafarnejadsani, Petros Voulgaris | Published: 2021-05-09 | Updated: 2021-05-17
Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly Generators
Authors: J. -P. Schulze, P. Sperl, K. Böttinger | Published: 2021-01-12 | Updated: 2024-01-14
Generating Natural Adversarial Hyperspectral examples with a modified Wasserstein GAN
Authors: Jean-Christophe Burnel, Kilian Fatras, Nicolas Courty | Published: 2020-01-27
HRFA: High-Resolution Feature-based Attack
Authors: Zhixing Ye, Sizhe Chen, Peidong Zhang, Chengjin Sun, Xiaolin Huang | Published: 2020-01-21 | Updated: 2020-10-22
Defending Neural Backdoors via Generative Distribution Modeling
Authors: Ximing Qiao, Yukun Yang, Hai Li | Published: 2019-10-10 | Updated: 2019-11-06
Membership Model Inversion Attacks for Deep Networks
Authors: Samyadeep Basu, Rauf Izmailov, Chris Mesterharm | Published: 2019-10-09
Adversarial Learning of Deepfakes in Accounting
Authors: Marco Schreyer, Timur Sattarov, Bernd Reimer, Damian Borth | Published: 2019-10-09
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions
Authors: He Zhao, Trung Le, Paul Montague, Olivier De Vel, Tamas Abraham, Dinh Phung | Published: 2019-10-03
GAMIN: An Adversarial Approach to Black-Box Model Inversion
Authors: Ulrich Aïvodji, Sébastien Gambs, Timon Ther | Published: 2019-09-26