Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks

被引：0

作者：

Ayaz, Ferheen ^{[3
]}

Zakariyya, Idris ^{[1
]}

Cano, José ^{[1
]}

Keoh, Sye Loong ^{[1
]}

Singer, Jeremy ^{[1
]}

Pau, Danilo ^{[2
]}

Kharbouche-Harrari, Mounia ^{[2
]}

机构：

[1] University of Glasgow, United Kingdom

[2] STMicroelectronics, Switzerland

[3] University of Sussex, United Kingdom

来源：

arXiv | 2023年

关键词：

Engineering Village;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Adversarial attack - Black boxes - Co-optimization - Deep neural network - Jacobian regularization - Jacobians - Neural network model - Qkera - Regularisation - White box

引用

共 50 条

[1] Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Ayaz, Ferheen
Zakariyya, Idris
Cano, Jose
Keoh, Sye Loong
Singer, Jeremy
Pau, Danilo
Kharbouche-Harrari, Mounia
2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, 2023,
[2] Relative Robustness of Quantized Neural Networks Against Adversarial Attacks
Duncan, Kirsty
Komendantskaya, Ekaterina
Stewart, Robert
Lones, Michael
2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
[3] Improving the adversarial robustness of quantized neural networks via exploiting the feature diversity
Chu, Tianshu
Fang, Kun
Yang, Jie
Huang, Xiaolin
PATTERN RECOGNITION LETTERS, 2023, 176 : 117 - 122
[4] Robustness Against Adversarial Attacks in Neural Networks Using Incremental Dissipativity
Aquino, Bernardo
Rahnama, Arash
Seiler, Peter
Lin, Lizhen
Gupta, Vijay
IEEE CONTROL SYSTEMS LETTERS, 2022, 6 : 2341 - 2346
[5] MRobust: A Method for Robustness against Adversarial Attacks on Deep Neural Networks
Liu, Yi-Ling
Lomuscio, Alessio
2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
[6] On the Robustness of Bayesian Neural Networks to Adversarial Attacks
Bortolussi, Luca
Carbone, Ginevra
Laurenti, Luca
Patane, Andrea
Sanguinetti, Guido
Wicker, Matthew
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, : 1 - 14
[7] ROBUSTNESS-AWARE FILTER PRUNING FOR ROBUST NEURAL NETWORKS AGAINST ADVERSARIAL ATTACKS
Lim, Hyuntak
Roh, Si-Dong
Park, Sangki
Chung, Ki-Seok
2021 IEEE 31ST INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2021,
[8] An orthogonal classifier for improving the adversarial robustness of neural networks
Xu, Cong
Li, Xiang
Yang, Min
INFORMATION SCIENCES, 2022, 591 : 251 - 262
[9] Improving Robustness of Facial Landmark Detection by Defending against Adversarial Attacks
Zhu, Congcong
Li, Xiaoqiang
Li, Jide
Dai, Songmin
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, : 11731 - 11740
[10] Bringing robustness against adversarial attacks
Gean T. Pereira
André C. P. L. F. de Carvalho
Nature Machine Intelligence, 2019, 1 : 499 - 500

← 1 2 3 4 5 →