Adversarial Attacks on Machine Learning Cybersecurity Defences in Industrial Control Systems
Authors: Eirini Anthi, Lowri Williams, Matilda Rhode, Pete Burnap, Adam Wedgbury | Published: 2020-04-10
攻撃の評価
Luring of transferable adversarial perturbations in the black-box paradigm
Authors: Rémi Bernhard, Pierre-Alain Moellic, Jean-Max Dutertre | Published: 2020-04-10 | Updated: 2021-03-03
TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
Authors: Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu | Published: 2020-04-09
Feature Partitioning for Robust Tree Ensembles and their Certification in Adversarial Scenarios
Authors: Stefano Calzavara, Claudio Lucchese, Federico Marcuzzi, Salvatore Orlando | Published: 2020-04-07
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
Authors: David Enthoven, Zaid Al-Ars | Published: 2020-04-01
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
Authors: David Stutz, Matthias Hein, Bernt Schiele | Published: 2019-10-14 | Updated: 2020-06-30
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Authors: Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu | Published: 2019-10-14 | Updated: 2019-10-27
Policy Poisoning in Batch Reinforcement Learning and Control
Authors: Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu | Published: 2019-10-13 | Updated: 2019-10-31
On Robustness of Neural Ordinary Differential Equations
Authors: Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng | Published: 2019-10-12 | Updated: 2022-03-03
Extraction of Complex DNN Models: Real Threat or Boogeyman?
Authors: Buse Gul Atli, Sebastian Szyller, Mika Juuti, Samuel Marchal, N. Asokan | Published: 2019-10-11 | Updated: 2020-05-27