Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks-Reference-Cited by-同舟云学术

Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Guan Zihan¹^ORCID,Sun Lichao²^ORCID,Du Mengnan³^ORCID,Liu Ninghao¹^ORCID

Affiliation:

1. University of Georgia, Athens, GA, USA

2. Lehigh University, Bethlehem, PA, USA

3. New Jersey Institute of Technology, Newark, NJ, USA

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3614784

Reference70 articles.

1. A New Backdoor Attack in CNNS by Training Set Corruption Without Label Poisoning

2. Weixin Chen Baoyuan Wu and Haoqian Wang. 2022. Effective Backdoor Defense by Exploiting Sensitivity of Poisoned Samples. In Advances in Neural Information Processing Systems Alice H. Oh Alekh Agarwal Danielle Belgrave and Kyunghyun Cho (Eds.). https://openreview.net/forum?id=AsH-Tx2U0Ug Weixin Chen Baoyuan Wu and Haoqian Wang. 2022. Effective Backdoor Defense by Exploiting Sensitivity of Poisoned Samples. In Advances in Neural Information Processing Systems Alice H. Oh Alekh Agarwal Danielle Belgrave and Kyunghyun Cho (Eds.). https://openreview.net/forum?id=AsH-Tx2U0Ug

3. Xinyun Chen , Chang Liu , Bo Li , Kimberly Lu , and Dawn Song . 2017. Targeted backdoor attacks on deep learning systems using data poisoning. arXiv preprint arXiv:1712.05526 ( 2017 ). Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song. 2017. Targeted backdoor attacks on deep learning systems using data poisoning. arXiv preprint arXiv:1712.05526 (2017).

4. Bao Gia Doan , Ehsan Abbasnejad , and Damith C. Ranasinghe . 2020 . Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems. In Annual Computer Security Applications Conference ( Austin, USA) (ACSAC '20). Association for Computing Machinery, New York, NY, USA, 897--912. https://doi.org/10.1145/3427228.3427264 10.1145/3427228.3427264 Bao Gia Doan, Ehsan Abbasnejad, and Damith C. Ranasinghe. 2020. Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems. In Annual Computer Security Applications Conference (Austin, USA) (ACSAC '20). Association for Computing Machinery, New York, NY, USA, 897--912. https://doi.org/10.1145/3427228.3427264

5. Khoa Doan , Yingjie Lao , Weijie Zhao , and Ping Li . 2021 . LIRA: Learnable , Imperceptible and Robust Backdoor Attacks. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 11946--11956 . https://doi.org/10.1109/ICCV48922.2021.01175 10.1109/ICCV48922.2021.01175 Khoa Doan, Yingjie Lao, Weijie Zhao, and Ping Li. 2021. LIRA: Learnable, Imperceptible and Robust Backdoor Attacks. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 11946--11956. https://doi.org/10.1109/ICCV48922.2021.01175