Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses
Authors: Shiliang Zuo | Published: 2020-08-21 | Updated: 2024-03-14
Attack Method
Defending Distributed Classifiers Against Data Poisoning Attacks
Authors: Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie | Published: 2020-08-21
Towards Class-Oriented Poisoning Attacks Against Neural Networks
Authors: Bingyin Zhao, Yingjie Lao | Published: 2020-07-31 | Updated: 2021-10-11
Adversarial Attacks with Multiple Antennas Against Deep Learning-Based Modulation Classifiers
Authors: Brian Kim, Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu, Sennur Ulukus | Published: 2020-07-31
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
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