A lightweight backdoor defense framework based on image inpainting
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Yufei Wang | Huan Liu | Haichang Gao | Yipeng Gao | Yier Wei
[1] Pengfei Xia,et al. Enhancing Backdoor Attacks With Multi-Level MMD Regularization , 2021, IEEE Transactions on Dependable and Secure Computing.
[2] A. Madry,et al. Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3] Hyoungshick Kim,et al. Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World , 2022, ArXiv.
[4] Yong Jiang,et al. Backdoor Learning: A Survey , 2020, IEEE transactions on neural networks and learning systems.
[5] Shanshan Peng,et al. Model Agnostic Defence Against Backdoor Attacks in Machine Learning , 2019, IEEE Transactions on Reliability.
[6] Sewoong Oh,et al. SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics , 2021, ArXiv.
[7] Simon S. Woo,et al. Neural Network Laundering: Removing Black-Box Backdoor Watermarks from Deep Neural Networks , 2020, Comput. Secur..
[8] Minhui Xue,et al. Invisible Backdoor Attacks on Deep Neural Networks Via Steganography and Regularization , 2019, IEEE Transactions on Dependable and Secure Computing.
[9] Tiberiu T. Cocias,et al. A survey of deep learning techniques for autonomous driving , 2019, J. Field Robotics.
[10] H. Pirsiavash,et al. Hidden Trigger Backdoor Attacks , 2019, AAAI.
[11] Bao Gia Doan,et al. Februus: Input Purification Defence Against Trojan Attacks on Deep Neural Network Systems , 2019, 1908.03369.
[12] Florian Tramèr,et al. SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems , 2018, 2020 IEEE Security and Privacy Workshops (SPW).
[13] Jishen Zhao,et al. DeepInspect: A Black-box Trojan Detection and Mitigation Framework for Deep Neural Networks , 2019, IJCAI.
[14] Dacheng Tao,et al. Perceptual-Sensitive GAN for Generating Adversarial Patches , 2019, AAAI.
[15] Ben Y. Zhao,et al. Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks , 2019, 2019 IEEE Symposium on Security and Privacy (SP).
[16] Damith Chinthana Ranasinghe,et al. STRIP: a defence against trojan attacks on deep neural networks , 2019, ACSAC.
[17] Wen-Chuan Lee,et al. NIC: Detecting Adversarial Samples with Neural Network Invariant Checking , 2019, NDSS.
[18] L. Deng,et al. The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web] , 2012, IEEE Signal Processing Magazine.
[19] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.