AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning
arxiv(2023)
摘要
This paper introduces AIJack, an open-source library designed to assess
security and privacy risks associated with the training and deployment of
machine learning models. Amid the growing interest in big data and AI,
advancements in machine learning research and business are accelerating.
However, recent studies reveal potential threats, such as the theft of training
data and the manipulation of models by malicious attackers. Therefore, a
comprehensive understanding of machine learning's security and privacy
vulnerabilities is crucial for the safe integration of machine learning into
real-world products. AIJack aims to address this need by providing a library
with various attack and defense methods through a unified API. The library is
publicly available on GitHub (https://github.com/Koukyosyumei/AIJack).
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要