One pixel attack for fooling deep neural networks J Su, DV Vargas, K Sakurai
IEEE Transactions on Evolutionary Computation 23 (5), 828-841, 2019
2620 2019 Lightweight classification of IoT malware based on image recognition J Su, DV Vasconcellos, S Prasad, D Sgandurra, Y Feng, K Sakurai
2018 IEEE 42Nd annual computer software and applications conference (COMPSAC …, 2018
354 2018 Spectrum-diverse neuroevolution with unified neural models DV Vargas, J Murata
IEEE transactions on neural networks and learning systems 28 (8), 1759-1773, 2016
56 2016 Attacking convolutional neural network using differential evolution J Su, DV Vargas, K Sakurai
IPSJ Transactions on Computer Vision and Applications 11, 1-16, 2019
50 2019 Understanding the one-pixel attack: Propagation maps and locality analysis DV Vargas, J Su
arXiv preprint arXiv:1902.02947, 2019
44 2019 Evolving robust neural architectures to defend from adversarial attacks DV Vargas, S Kotyan, SPM IIIT-NR
arXiv preprint arXiv:1906.11667 3, 2019
23 2019 General subpopulation framework and taming the conflict inside populations DV Vargas, J Murata, H Takano, ACB Delbem
Evolutionary computation 23 (1), 1-36, 2015
23 2015 Neural cryptography based on the topology evolving neural networks Y Zhu, DV Vargas, K Sakurai
2018 Sixth International Symposium on Computing and Networking Workshops …, 2018
22 2018 Adversarial robustness assessment: Why in evaluation both L 0 and L ∞ attacks are necessary S Kotyan, DV Vargas
Plos one 17 (4), e0265723, 2022
21 2022 Self organizing classifiers and niched fitness DV Vargas, H Takano, J Murata
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
21 2013 Tracing MIRAI malware in networked system Y Xu, H Koide, DV Vargas, K Sakurai
2018 sixth international symposium on computing and networking workshops …, 2018
20 2018 Towards evolving robust neural architectures to defend from adversarial attacks S Kotyan, DV Vargas
Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020
19 2020 Robustness assessment for adversarial machine learning: Problems, solutions and a survey of current neural networks and defenses DV Vargas, S Kotyan
arXiv preprint arXiv:1906.06026, 2019
16 2019 Batch tournament selection for genetic programming: the quality of lexicase, the speed of tournament VV De Melo, DV Vargas, W Banzhaf
Proceedings of the genetic and evolutionary computation conference, 994-1002, 2019
15 2019 Self organizing classifiers: first steps in structured evolutionary machine learning DV Vargas, H Takano, J Murata
Evolutionary Intelligence 6, 57-72, 2013
15 2013 Novelty-organizing team of classifiers in noisy and dynamic environments DV Vargas, H Takano, J Murata
2015 IEEE Congress on Evolutionary Computation (CEC), 2937-2944, 2015
13 2015 Multi-objective phylogenetic algorithm: Solving multi-objective decomposable deceptive problems JP Martins, AHM Soares, DV Vargas, ACB Delbem
International Conference on Evolutionary Multi-Criterion Optimization, 285-297, 2011
13 2011 Adversarial Robustness Assessment: Why both and Attacks Are Necessary S Kotyan, DV Vargas
arXiv preprint arXiv:1906.06026, 2019
12 2019 One Pixel Attack for Fooling Deep Neural Networks. 2017 J Su, DV Vargas, K Sakurai
Режим доступа: https://arxiv. org/pdf/1710.08864. pdf, 2019
12 2019 Universal rules for fooling deep neural networks based text classification D Li, DV Vargas, S Kouichi
2019 IEEE Congress on Evolutionary Computation (CEC), 2221-2228, 2019
11 2019