TEAM: We Need More Powerful Adversarial Examples for DNNs
Authors: Yaguan Qian, Ximin Zhang, Bin Wang, Wei Li, Zhaoquan Gu, Haijiang Wang, Wassim Swaileh | Published: 2020-07-31 | Updated: 2020-08-10
Attack Method
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
Membership Leakage in Label-Only Exposures
Authors: Zheng Li, Yang Zhang | Published: 2020-07-30 | Updated: 2021-09-17
Black-box Adversarial Sample Generation Based on Differential Evolution
Authors: Junyu Lin, Lei Xu, Yingqi Liu, Xiangyu Zhang | Published: 2020-07-30
A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Authors: Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee | Published: 2020-07-29 | Updated: 2021-06-17
Adversarial Robustness for Machine Learning Cyber Defenses Using Log Data
Authors: Kai Steverson, Jonathan Mullin, Metin Ahiskali | Published: 2020-07-29
Label-Only Membership Inference Attacks
Authors: Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot | Published: 2020-07-28 | Updated: 2021-12-05
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning
Authors: Jirong Yi, Raghu Mudumbai, Weiyu Xu | Published: 2020-07-28
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
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