AIJack: Security and Privacy Risk Simulator for Machine Learning. (arXiv:2312.17667v1 [cs.LG])

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 …

big big data big data and ai business data deployment interest library machine machine learning machine learning models potential threats privacy privacy risk privacy risks research reveal risk risks security simulator studies threats training