{"repo":"AI-SDC/SACRO-ML","free":true,"listed":false,"github":"https://github.com/AI-SDC/SACRO-ML","clone":"git clone https://github.com/AI-SDC/SACRO-ML.git","description":"Collection of tools and resources for managing the statistical disclosure control of trained machine learning models","language":"Python","stars":40,"topics":["attribute-inference-attack","data-privacy","data-protection","inference","machine-learning","membership-inference-attack","privacy","differential-privacy","statistical-disclosure-control"],"license":"MIT","category":"machine-learning","readme_excerpt":"SACRO-ML: Disclosure Control Tools for ML Models An increasing body of work has shown that machine learning (ML) models may expose confidential properties of the data on which they are trained. This has resulted in a wide range of proposed attack methods with varying assumptions that exploit the model structure and/or behaviour to infer sensitive information. The sacroml package is a collection of tools and resources for managing the statistical disclosure control (SDC) of trained ML models. In particular, it provides: A safemodel package that extends commonly used ML models to provide ante-hoc SDC by assessing the theoretical risk posed by the training regime (such as hyperparameter, dataset, and architecture combinations) before (potentially) costly model fitting is performed. In addition, it ensures that best practice is followed with respect to privacy, e.g., using differential privacy optimisers where available. For large models and datasets, ante-hoc analysis has the potential for significant time and cost savings by helping to avoid wasting resources training models that are likely to be found to be disclosive after running intensive post-hoc analysis. An attacks package that provides post-hoc SDC by assessing the empirical disclosure risk of a classification model through a variety of simulated attacks after training. It provides an integrated suite of attacks with a common application programming interface (API) and is designed to support the inclusion of additional ","default_branch":null,"files":null,"tree":[],"storefront":"/r/AI-SDC","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AI-SDC/SACRO-ML/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}