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Adversarial Machine Learning: Difficulties in Applying Machine Learning to Existing Cybersecurity Systems

机译：对抗机器学习：将机器学习应用于现有网络安全系统的困难

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Nick Rahimi; Jordan Maynor; Bidyut Gupta;
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1. Adversarial attacks on machine learning cybersecurity defences in Industrial Control Systems [J] . Anthi Eirini, Williams Lowri, Rhode Matilda, Journal of information security and applications . 2021,第May期

机译：对工业控制系统中机器学习网络安全防御的对抗攻击
2. A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks [J] . Dasgupta Prithviraj, Collins Joseph B. AI Magazine . 2019,第2期

机译：网络安全任务中对抗性机器学习的博弈论方法研究
3. A Survey of Game Theoretic Approaches for Adversarial Machine Learning in Cybersecurity Tasks [J] . Dasgupta Prithviraj, Collins Joseph B. AI Magazine . 2019,第2期

机译：对网络安全任务的对抗机器学习游戏理论方法调查
4. Adversarial Machine Learning: Difficulties in Applying Machine Learning Existing Cybersecurity Systems [C] . Nick Rahimi, Jordan Maynor, Bidyut Gupta International Conference on Computers and Their Applications . 2020

机译：对抗机器学习：应用机器学习现有网络安全系统的困难
5. Adversarial Machine Learning in Computer Vision: Attacks and Defenses on Machine Learning Models [D] . Qin, Yi. 2021

机译：计算机视觉上的对抗机器学习：机器学习模型的攻击和防御
6. Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review [O] . Lea Marie Pehrson, Michael Bachmann Nielsen, Carsten Ammitzbøl Lauridsen 2019

机译：将深度学习或机器学习算法应用于LIDC-IDRI数据库的自动肺结节检测：系统综述
7. Adversarial attacks on machine learning cybersecurity defences in Industrial Control Systems [O] . Eirini Anthi, Lowri Williams, Matilda Rhode, 2021

机译：对工业控制系统中机器学习网络安全防御的对抗攻击

Adversarial Machine Learning: Difficulties in Applying Machine Learning to Existing Cybersecurity Systems

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