{"id":26397354,"url":"https://github.com/thalesgroup/secure-ml","last_synced_at":"2026-01-04T13:01:57.899Z","repository":{"id":256910469,"uuid":"781383606","full_name":"ThalesGroup/secure-ml","owner":"ThalesGroup","description":"Explore ThalesGroup's comprehensive framework for secure machine learning systems on this repository. 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This policy outlines activities, responsibilities, and guidelines to protect ML models, data, and infrastructure from unauthorized access, malicious attacks, and privacy breaches.\n\nAvailable at [ML Security Policy](security-policy/ml-secpol.md) with [ML Security Requirements](security-policy/ml-secpol-detailed.md) and [ML Security Guidelines](security-policy/guidelines/ml-secpol-guidelines.md)\n\n## Machine Learning Privacy-Preserving Techniques\nLearn about cutting-edge privacy-preserving techniques for machine learning including Differential Privacy, Federated Learning, Homomorphic Encryption, Secure Multi-Party Computation (SMPC), and Privacy-Preserving Data Synthesis in this comprehensive GitHub repository. Explore how these methods safeguard sensitive data while enabling collaborative analysis and model training.\n\nAvailable at [ML privacy-preserving techniques](privacy/ml-privacy-techniques.md)\n\n## Tools for Securing Machine Learning\n\nDiscover essential security tools for source code vulnerability detection, comprehensive attack and defense tools, ML supply chain security solutions, and privacy and compliance tools. Additionally, explore techniques for securing Jupyter notebooks, ensuring robust protection for your data, code, and models. Embrace a holistic approach to cybersecurity and data privacy in your development and analysis workflows.\n\nAvailable at [ML security tools](tools/ml-security-tools.md)\n\n## Security Threats to Machine Learning\n\nAvailable at [ML Security Threats](ml-threats/ml-threats.md)\n\n## Presentation on ML Security Risks, Policy, Tools, Privacy techniques and more\n\n- **Conference**: OWASP LASCON 2024\n- **Agenda**: ML lifecycle/workflow, AI for Cyber vs Cyber for AI, Cyber Attacks, Risks, Threats, Thales Security Framework, Recommendations and more.\n\n\u003ca href=\"https://youtu.be/vcRsGlrsFjs?si=WSaQUe9-bNpNEHEc\u0026t=58\" target=\"_blank\"\u003e\n  \u003cimg src=\"images/lascon2024.png\" \n       alt=\"Watch the video\" \n       title=\"Watch the video\" \n       style=\"width:600px;\"\u003e\n\u003c/a\u003e\n\nYou can access the presentation deck (PDF) at \n[View Documentation (PDF)](presentations/ML_SecPlan.pdf) and other interesting [documents](documents/documents.md) for your reading.\n\n\n## License\n\n![License: CC BY-ND 4.0](https://img.shields.io/badge/License-CC_BY--ND_4.0-lightgrey.svg)\n\nThis project is licensed under the Creative Commons Attribution-NoDerivs 4.0 International (CC BY-ND 4.0) License. \nYou can view the full license text [here](https://creativecommons.org/licenses/by-nd/4.0/legalcode).\n\n## Project Contacts\n\nFor further information or to contribute to this project, you can reach out to the following contacts:\n\n- **Project Leader and Key contributor:** Viswanath S Chirravuri  \n  [LinkedIn](https://www.linkedin.com/in/chviswanath/)\n\n- **Project Sponsors:**\n  - Gilles Durbec  \n    [LinkedIn](https://fr.linkedin.com/in/gilles-durbec-1435412)\n  - Stephane Soustre  \n    [LinkedIn](https://www.linkedin.com/in/stephane-soustre-09a10b2/)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthalesgroup%2Fsecure-ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthalesgroup%2Fsecure-ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthalesgroup%2Fsecure-ml/lists"}