后门攻击
知乎问答 & 公众号：
- 后门学习(Backdoor Learning)介绍及资源汇总
- 浅谈深度学习后门攻击
- Backdoor Learning: A SurveyAI中的后门攻击及防御-实战篇
- 如何攻击深度学习系统——后门攻防
- 毒墨水：一种隐蔽且鲁棒的后门攻击
- 深度学习中的后门攻击综述【 信 息 安 全 学 报】
- 对深度学习模型的后门攻击在现实世界中是否可行？
- 如何保护深度学习系统-后门防御
- 复旦大学｜基于文本风格的隐式NLP后门攻击（USENIX-SEC 2022）
- 联邦学习中的后门攻击
- 医疗图像后门攻击的解释
- 每周论文讨论(8) | 图神经网络后门攻击
- BadNets-深度学习后门攻击的开篇之作
- 【直播】【AI TIME】回顾与展望神经网络的后门攻击与防御
paper
- Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
- Dynamic Backdoor Attacks Against Machine Learning Models
- Backdoor Attacks Against Deep Learning Systems in the Physical World
- Backdoor Learning: A Survey
GitHub paper resource:
- backdoor learning resource
- OpenBackdoor
对抗攻击
- 综述论文：对抗攻击的12种攻击方法和15种防御方法
- 一文尽览！文本对抗攻击基础、前沿及相关资源
- CV||对抗攻击领域综述（adversarial attack）
- 针对深度学习的对抗攻击综述
- 人工智能对抗攻击研究综述
- 文本对抗攻击之综述
- 对抗样本（一）以综述入门
- OpenAttack：文本对抗攻击工具包
- 什么是nlp中的对抗示例
- 面向自然语言处理的对抗攻防与鲁棒性分析综述
- 基于梯度的NLP对抗攻击方法
paper：
- Adversarial Attack and Defense: A Survey
- Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
- A survey on adversarial attacks and defences
- A Survey on Universal Adversarial Attack
- Adversarial Attacks and Defences: A Survey
- Adversarial Attack and Defense on Graph Data: A Survey
- Towards More Practical Adversarial Attacks on Graph Neural Networks
- GNNGUARD: Defending Graph Neural Networks against Adversarial Attacks
- Adversarial Attacks on Graph Neural Networks via Meta Learning
- Adversarial Attacks on Deep-learning Models in Natural Language Processing: A Survey
- A survey of Adversarial Defences and Robustness in NLP
- Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey
github：
-
Must-read Papers on Textual Adversarial Attack and Defense (TAAD)
-
Adversarial-Attack-Papers
-
The Papers of Adversarial Examples文章来源：https://www.toymoban.com/news/detail-492421.html
tools:文章来源地址https://www.toymoban.com/news/detail-492421.html
- https://pytorch.org/tutorials/beginner/fgsm_tutorial.html
- Adversarial-Attacks-PyTorch
- Open attack
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