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# Release 0.1.0-alpha
Initial release of MindArmour.
## Major Features
- Support adversarial attack and defense on the platform of MindSpore.
- Include 13 white-box and 7 black-box attack methods.
- Provide 5 detection algorithms to detect attacking in multiple way.
- Provide adversarial training to enhance model security.
- Provide 6 evaluation metrics for attack methods and 9 evaluation metrics for defense methods.
MindArmour关注AI的安全和隐私问题。致力于增强模型的安全可信、保护用户的数据隐私。主要包含3个模块:对抗样本鲁棒性模块、Fuzz Testing模块、隐私保护与评估模块。
对抗样本鲁棒性模块
对抗样本鲁棒性模块用于评估模型对于对抗样本的鲁棒性,并提供模型增强方法用于增强模型抗对抗样本攻击的能力,提升模型鲁棒性。对抗样本鲁棒性模块包含了4个子模块:对抗样本的生成、对抗样本的检测、模型防御、攻防评估。