Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases
Authors: Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang | Published: 2020-07-31
Poisoning
Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning
Authors: Nuria Rodríguez-Barroso, Eugenio Martínez-Cámara, M. Victoria Luzón, Francisco Herrera | Published: 2020-07-29 | Updated: 2022-02-24
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review
Authors: Yansong Gao, Bao Gia Doan, Zhi Zhang, Siqi Ma, Jiliang Zhang, Anmin Fu, Surya Nepal, Hyoungshick Kim | Published: 2020-07-21 | Updated: 2020-08-02
Adversarial Immunization for Certifiable Robustness on Graphs
Authors: Shuchang Tao, Huawei Shen, Qi Cao, Liang Hou, Xueqi Cheng | Published: 2020-07-19 | Updated: 2021-08-25
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
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