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We Need to Talk About Robustness to Adversarial Attacks while Removing Spurious Dataset Biases

机译：我们需要在删除虚假数据集偏见时讨论对抗性攻击的鲁棒性

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作者
Sachdeva, Bhavdeep Singh.;
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作者单位

Arizona State University.;

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授予单位 Arizona State University.;
学科
学位 M.S.
年度 2021
页码 73 p.
总页数 73
原文格式 PDF
正文语种 eng
中图分类
关键词
入库时间 2022-08-17 12:03:51

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1. DReLAB - Deep REinforcement Learning Adversarial Botnet: A benchmark dataset for adversarial attacks against botnet Intrusion Detection Systems [J] . Andrea Venturi, Giovanni Apruzzese, Mauro Andreolini, Data in Brief . 2021,第3期

机译：DRELAB - 深度加强学习对抗僵尸网络：用于对僵尸网络入侵检测系统进行对抗性攻击的基准数据集
2. Robust Graph Neural Networks Against Adversarial Attacks via Jointly Adversarial Training [J] . Hu Tian, Bowei Ye, Xiaolong Zheng, IFAC PapersOnLine . 2020,第5期

机译：通过共同对抗培训，强大的图形神经网络对抗对抗攻击
3. Injecting and removing suspicious features in breast imaging with CycleGAN: A pilot study of automated adversarial attacks using neural networks on small images [J] . Becker Anton S., Jendele Lukas, Skopek Ondrej, European Journal of Radiology . 2019,第期

机译：用Crycangan注入和消除乳房成像中的可疑特征：使用小幅上的神经网络自动对抗攻击的试验研究
4. Adversarial Filters of Dataset Biases [C] . Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, International Conference on Machine Learning . 2021

机译：数据集偏差的对抗筛选器
5. Adversarial Attacks and Robustness in Deep Learning Models and Applications [D] . Alparslan, Yigit Can. 2021

机译：深度学习模型和应用中的对抗攻击和鲁棒性
6. DReLAB - Deep REinforcement Learning Adversarial Botnet: A benchmark dataset for adversarial attacks against botnet Intrusion Detection Systems [O] . Andrea Venturi, Giovanni Apruzzese, Mauro Andreolini, 2021

机译：DRELAB - 深度加强学习对抗僵尸网络：用于对僵尸网络入侵检测系统进行对抗性攻击的基准数据集
7. Blind Adversarial Pruning: Towards The Comprehensive Robust Models With Gradually Pruning Against Blind Adversarial Attacks [O] . Haidong Xie, Lixin Qian, Xueshuang Xiang, 2021

机译：盲体对抗修剪：朝着逐渐修剪逐渐修剪盲目对抗攻击的综合策略模型

We Need to Talk About Robustness to Adversarial Attacks while Removing Spurious Dataset Biases

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