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EvoBA: An Evolution Strategy as a Strong Baseline forBlack-Box
  Adversarial Attacks

EvoBA: An Evolution Strategy as a Strong Baseline forBlack-Box Adversarial Attacks

12 July 2021
Andrei-Șerban Ilie
Marius Popescu
Alin Stefanescu
    AAML
ArXivPDFHTML

Papers citing "EvoBA: An Evolution Strategy as a Strong Baseline forBlack-Box Adversarial Attacks"

3 / 3 papers shown
Title
EGAN: Evolutional GAN for Ransomware Evasion
EGAN: Evolutional GAN for Ransomware Evasion
Daniel Commey
Benjamin Appiah
B. K. Frimpong
Isaac Osei
Ebenezer N. A. Hammond
Garth V. Crosby
AAML
GAN
19
0
0
20 May 2024
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise
  Regression Tasks
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks
Zhiyuan Cheng
Zhaoyi Liu
Tengda Guo
Shiwei Feng
Dongfang Liu
Mingjie Tang
Xiangyu Zhang
AAML
27
3
0
01 Apr 2024
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
883
0
21 Oct 2016
1