> For the complete documentation index, see [llms.txt](https://rice-ai.gitbook.io/home/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://rice-ai.gitbook.io/home/technical-deepdive/privacy-and-security-measures.md).

# Privacy and Security Measures

* Personal Custody: Data are held on the user's own robot unless the user decides to share it.
* Federated Learning: Apply federated learning to allow AI models to train on data locally without transferring raw data.
* Data Encryption: End-to-end encryption to secure data during transmission and storage on decentralized nodes.
* Access Controls: Role-based access controls to ensure only authorized personnel can access sensitive data.
* Data Anonymization: We have special techniques to anonymize data, ensuring that individual identities cannot be traced—for example, built-in local algorithms that blur out faces.
* Consent Management: Ensure that users have full control over their data with clear consent mechanisms and the ability to revoke access.


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