Black-box Adversarial Sample Generation Based on Differential Evolution

Black-box Adversarial Sample Generation Based on Differential Evolution

30 July 2020

Papers citing "Black-box Adversarial Sample Generation Based on Differential Evolution"

9 / 9 papers shown

Title
Universal Multi-view Black-box Attack against Object Detectors via Layout Optimization Donghua Wang Wen Yao Tingsong Jiang Chao Li Xiaoqian Chen AAML 52 0 0 09 Jul 2024
Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances Emma Hart Quentin Renau Kevin Sim M. Alissa AAML 35 0 0 24 Jun 2024
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection João Vitorino Isabel Praça Eva Maia AAML 30 22 0 13 Aug 2023
An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Networks Raz Lapid Zvika Haramaty Moshe Sipper AAML MLAU 25 12 0 17 Aug 2022
A Search-Based Testing Approach for Deep Reinforcement Learning Agents Amirhossein Zolfagharian Manel Abdellatif Lionel C. Briand M. Bagherzadeh Ramesh S 50 27 0 15 Jun 2022
Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection João Vitorino Nuno Oliveira Isabel Praça AAML 27 28 0 08 Mar 2022
Automatic Test Suite Generation for Key-Points Detection DNNs using Many-Objective Search (Experience Paper) Fitash Ul Haq Donghwan Shin Lionel C. Briand Thomas Stifter Jun Wang AAML 21 19 0 11 Dec 2020
A Survey on Deep Learning in Medical Image Analysis G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi Mohsen Ghafoorian Jeroen van der Laak Bram van Ginneken C. I. Sánchez OOD 343 10,639 0 19 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 332 5,849 0 08 Jul 2016