intelligent-security-competition's Introduction

Intelligent-Security-Competition

🐟背景

通过引入对抗样本，攻击者很容易就可以通过肉眼几乎观察不到的微小扰动，使模型分类失误。

🚀主要贡献

防御模型的集成可以在一定程度上提高整体的鲁棒性，我们决定同时集成来自ARES库的6个防御模型和RoubustBench排行榜上的4个防御模型
攻击方法选择了包含L2PGD攻击方法在内的组合攻击方法AutoAttack，用于攻击模型以生成对抗样本
二分空间中，最优参数搜索和参数动态适应优化

🚲实验结果

在《 Cifar-10 数字世界无限制对抗攻击竞赛》中排名TOP1

❗声明

相关模型权重和关键代码未上传，后续课程禁止复用抄袭本仓库代码

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