We present AI-SDC, an integrated suite of open source Python tools to facilitate Statistical Disclosure Control (SDC) of Machine Learning (ML) models trained on confidential data prior to public release. AI-SDC combines (i) a SafeModel package that extends commonly used ML models to provide ante-hoc SDC by assessing the vulnerability of disclosure posed by the training regime; and (ii) an Attacks package that provides post-hoc SDC by rigorously assessing the empirical disclosure risk of a model through a variety of simulated attacks after training. The AI-SDC code and documentation are available under an MIT license at https://github.com/AI-SDC/AI-SDC.
翻译:我们介绍了AI-SDC,这是一套综合的开放源码Python工具,用于便利在公开发布之前接受过保密数据培训的机器学习模型的统计披露控制(SDC),AI-SDC综合了(一)一个安全模型包,扩展了常用的ML模型,通过评估培训制度造成的披露脆弱性,提供前置SDC;和(二)一个攻击包,通过严格评估培训后各种模拟攻击后模型的经验披露风险,提供后置SDC。 AI-SDC代码和文件根据麻省理工学院的许可证可在https://github.com/AI-SDC/AI-SDC查阅。