Forming Adversarial Example Attacks Against Deep Neural Networks With Reinforcement Learning

被引：0

作者：

Akers, Matthew ^{[1
]}

Barton, Armon ^{[2
]}

机构：

[1] US Second Fleet, Hampton Rd, Norfolk, VA 23455 USA

[2] Dept Comp Sci Naval Postgrad Sch, Dept Comp Sci, Monterey, CA 93943 USA

来源：

COMPUTER | 2024年 / 57卷 / 01期

关键词：

Deep learning; Perturbation methods; Reinforcement learning; Artificial neural networks; GAME; GO;

D O I：

10.1109/MC.2023.3324751

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a novel reinforcement learning-based adversarial example attack, Adversarial Reinforcement Learning Agent, designed to learn imperceptible perturbation that causes misclassification when added to the input of a deep learning classifier.

引用

页码：88 / 99

页数：12

共 50 条

[41] Defenses Against Byzantine Attacks in Distributed Deep Neural Networks
Xia, Qi
Tao, Zeyi
Li, Qun
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2021, 8 (03): : 2025 - 2035
[42] STRIP: A Defence Against Trojan Attacks on Deep Neural Networks
Gao, Yansong
Xu, Change
Wang, Derui
Chen, Shiping
Ranasinghe, Damith C.
Nepal, Surya
35TH ANNUAL COMPUTER SECURITY APPLICATIONS CONFERENCE (ACSA), 2019, : 113 - 125
[43] Performance Enhancement of Deep Reinforcement Learning Networks Using Feature Extraction
Ollero, Joaquin
Child, Christopher
ADVANCES IN NEURAL NETWORKS - ISNN 2018, 2018, 10878 : 208 - 218
[44] Deep Adversarial Reinforcement Learning With Noise Compensation by Autoencoder
Ohashi, Kohei
Nakanishi, Kosuke
Sasaki, Wataru
Yasui, Yuji
Ishii, Shin
IEEE ACCESS, 2021, 9 : 143901 - 143912
[45] Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy
Mo, Kanghua
Tang, Weixuan
Li, Jin
Yuan, Xu
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2023, 20 (01) : 758 - 768
[46] Physical Adversarial Attacks Against Deep Learning Based Channel Decoding Systems
Babu, Surabhi Ashok
Ameer, P. M.
2020 IEEE REGION 10 SYMPOSIUM (TENSYMP) - TECHNOLOGY FOR IMPACTFUL SUSTAINABLE DEVELOPMENT, 2020, : 1511 - 1514
[47] Adversarial Deep Learning: A Survey on Adversarial Attacks and Defense Mechanisms on Image Classification
Khamaiseh, Samer Y.
Bagagem, Derek
Al-Alaj, Abdullah
Mancino, Mathew
Alomari, Hakam W.
IEEE ACCESS, 2022, 10 : 102266 - 102291
[48] Evasion Attacks with Adversarial Deep Learning Against Power System State Estimation
Sayghe, Ali
Zhao, Junbo
Konstantinou, Charalambos
2020 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2020,
[49] Robust Adversarial Attacks on Deep Learning-Based RF Fingerprint Identification
Liu, Boyang
Zhang, Haoran
Wan, Yiyao
Zhou, Fuhui
Wu, Qihui
Ng, Derrick Wing Kwan
IEEE WIRELESS COMMUNICATIONS LETTERS, 2023, 12 (06) : 1037 - 1041
[50] Assessing the Threat of Adversarial Examples on Deep Neural Networks for Remote Sensing Scene Classification: Attacks and Defenses
Xu, Yonghao
Du, Bo
Zhang, Liangpei
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (02): : 1604 - 1617

← 1 2 3 4 5 →