{"repo":"scimorph/secureml","free":true,"listed":false,"github":"https://github.com/scimorph/secureml","clone":"git clone https://github.com/scimorph/secureml.git","description":"Easy-to-use utilities to build privacy-preserving AI.","language":"Python","stars":35,"topics":["ai","click","compliance","gdpr","jinja2","ml","privacy","python","yaml","opacus"],"license":"MIT","category":"machine-learning","readme_excerpt":"Documentation SecureML is an open-source Python library that integrates with popular machine learning frameworks like TensorFlow and PyTorch. It provides developers with easy-to-use utilities to ensure that AI agents handle sensitive data in compliance with data protection regulations. Key Features - Data Anonymization Utilities : - K-anonymity implementation with adaptive generalization - Pseudonymization with format-preserving encryption - Configurable data masking with statistical property preservation - Hierarchical data generalization with taxonomy support - Automatic sensitive data detection - Privacy-Preserving Training Methods : - Differential privacy integration with PyTorch (via Opacus) and TensorFlow (via TF Privacy) - Federated learning with Flower, allowing training on distributed data without centralization - Support for secure aggregation and privacy-preserving federated learning - Compliance Checkers : Tools to analyze datasets and model configurations for potential privacy risks - Synthetic Data Generation : - Multiple generation methods including statistical modeling, GANs, and copulas - SDV integration with Gaussian Copula, CTGAN, and TVAE synthesizers - Automatic sensitive data detection and special handling - Preservation of statistical properties and correlations between variables - Support for mixed data types (numeric, categorical, datetime) - Configurable privacy-utility tradeoff controls - Tabular data synthesis with relation preservation - Regulatio","default_branch":null,"files":null,"tree":[],"storefront":"/r/scimorph","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/scimorph/secureml/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."}