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Reverse engineering imperceptible backdoor attacks on deep neural networks for detection and training set cleansing

机译：逆向工程难以察觉的后门攻击深神经网络检测和训练洁面

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Zhen Xiang; David J. Miller; George Kesidis;
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年度 2021
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1. Reverse engineering imperceptible backdoor attacks on deep neural networks for detection and training set cleansing [J] . Zhen Xiang, David J. Miller, George Kesidis Computers & Security . 2021,第Jula期

机译：逆向工程难以察觉的后门攻击深神经网络检测和培训洁面
2. Multi-Targeted Backdoor: Indentifying Backdoor Attack for Multiple Deep Neural Networks [J] . Hyun KWON, Hyunsoo YOON, Ki-Woong PARK IEICE transactions on information and systems . 2020,第4期

机译：多目标后门：缩写多个深神经网络的后门攻击
3. Neural network laundering: Removing black-box backdoor watermarks from deep neural networks [J] . William Aiken, Hyoungshick Kim, Simon Woo, Computers & Security . 2021,第Jula期

机译：神经网络洗涤：从深神经网络中删除黑匣子后门水印
4. L-Red: Efficient Post-Training Detection of Imperceptible Backdoor Attacks Without Access to the Training Set [C] . Zhen Xiang, David J. Miller, George Kesidis IEEE International Conference on Acoustics, Speech and Signal Processing . 2021

机译：L-RED：高效训练后的难以察觉的后门攻击攻击，无需访问培训集
5. A framework for reverse TCP backdoor attack and computer forensic on Linux OS [D] . Odumosu, Joshua O. 2016

机译：在Linux OS上反向TCP后门攻击和计算机法医的框架
6. A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations [O] . Holger R. Roth, Le Lu, Ari Seff, -1

机译：使用深度卷积神经网络观测值的随机集的淋巴结检测的新2.5D表示
7. Multi-Targeted Backdoor: Indentifying Backdoor Attack for Multiple Deep Neural Networks [O] . Hyun KWON, Hyunsoo YOON, Ki-Woong PARK 2020

机译：多目标后门：缩写多个深神经网络的后门攻击

Reverse engineering imperceptible backdoor attacks on deep neural networks for detection and training set cleansing

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