OpenAI News·· 2017-02-24AI 评分21
OpenAI 解析对抗样本攻击机器学习原理
Attacking machine learning with adversarial examples
AI 导读
OpenAI 展示对抗样本如何作为输入导致机器学习模型出错,其机制类似机器版的光学错觉。文章分析了不同媒介中对抗样本的工作原理,并探讨了为何防御此类攻击以保障系统安全极具挑战性。
原文
Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to cause the model to make a mistake; they’re like optical illusions for machines. In this post we’ll show how adversarial examples work across different mediums, and will discuss why securing systems against them can be difficult.
来源:OpenAI News · openai.com