TY - GEN
T1 - An Adversarial Attack Based on Multi-objective Optimization in the Black-Box Scenario
T2 - 21st International Conference on Information and Communications Security, ICICS 2019
AU - Zhang, Chunkai
AU - Deng, Yepeng
AU - Guo, Xin
AU - Wang, Xuan
AU - Liu, Chuanyi
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Various approaches have been proposed to exploit the vulnerability to challenge the robustness of victim models, in the black-box scenario, it is difficult to generate barely noticeable adversarial examples while guaranteeing the attack success rate. Although some methods could solve this problem to some extent, the imperceptibility of the generated perturbations is still far from that of the most advanced attack, worse still, it is infeasible to attack the color image datasets due to its inefficiency. In MOEA-APGA II, We propose the new objective function and the novel population evolution strategies to reduce the average distortion without sacrificing the attack success rate, and compared to the state-of-the-art black-box attack (ZOO), our method achieves a better attack success rate under fewer queries on the benchmark datasets.
AB - Various approaches have been proposed to exploit the vulnerability to challenge the robustness of victim models, in the black-box scenario, it is difficult to generate barely noticeable adversarial examples while guaranteeing the attack success rate. Although some methods could solve this problem to some extent, the imperceptibility of the generated perturbations is still far from that of the most advanced attack, worse still, it is infeasible to attack the color image datasets due to its inefficiency. In MOEA-APGA II, We propose the new objective function and the novel population evolution strategies to reduce the average distortion without sacrificing the attack success rate, and compared to the state-of-the-art black-box attack (ZOO), our method achieves a better attack success rate under fewer queries on the benchmark datasets.
KW - Adversarial examples
KW - Black-box attack
KW - Multi-objective optimization
UR - https://www.scopus.com/pages/publications/85081180161
U2 - 10.1007/978-3-030-41579-2_35
DO - 10.1007/978-3-030-41579-2_35
M3 - 会议稿件
AN - SCOPUS:85081180161
SN - 9783030415785
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 603
EP - 612
BT - Information and Communications Security - 21st International Conference, ICICS 2019, Revised Selected Papers
A2 - Zhou, Jianying
A2 - Luo, Xiapu
A2 - Shen, Qingni
A2 - Xu, Zhen
PB - Springer
Y2 - 15 December 2019 through 17 December 2019
ER -