Data Poisoning Attacks Against Federated Learning Systems
Authors: Vale Tolpegin, Stacey Truex, Mehmet Emre Gursoy, Ling Liu | Published: 2020-07-16 | Updated: 2020-08-11
Poisoning
A simple defense against adversarial attacks on heatmap explanations
Authors: Laura Rieger, Lars Kai Hansen | Published: 2020-07-13
Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification
Authors: Chuanshuai Chen, Jiazhu Dai | Published: 2020-07-11 | Updated: 2021-03-15
Improving Adversarial Robustness by Enforcing Local and Global Compactness
Authors: Anh Bui, Trung Le, He Zhao, Paul Montague, Olivier deVel, Tamas Abraham, Dinh Phung | Published: 2020-07-10
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
Authors: Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris Papailiopoulos | Published: 2020-07-09
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs
Authors: Rana Abou Khamis, Ashraf Matrawy | Published: 2020-07-08
On the relationship between class selectivity, dimensionality, and robustness
Authors: Matthew L. Leavitt, Ari S. Morcos | Published: 2020-07-08 | Updated: 2020-10-13
Backdoor attacks and defenses in feature-partitioned collaborative learning
Authors: Yang Liu, Zhihao Yi, Tianjian Chen | Published: 2020-07-07
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Authors: Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus, Verena Haunschmid, Michal Lewandowski, Werner Zellinger, Bernhard A. Moser, Gerhard Widmer | Published: 2020-07-06
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
Authors: Samuel Henrique Silva, Peyman Najafirad | Published: 2020-07-01 | Updated: 2020-07-03