I’m working on several machine-learning projects and regularly sync training results, logs, and datasets to shared project spaces. Since some of this work is done directly on my AI laptop, I want to make sure that any sensitive model outputs, experiment notes, or proprietary datasets remain fully protected during both transfer and storage.
I’d love to hear how others are handling this. Specifically:
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Do you use encrypted folders or drives on your AI laptop before syncing?
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What security methods or tools do you rely on when transferring files to shared environments?
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Is version control (Git, DVC, etc.) safe enough when used with sensitive data?
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How do you manage access control so only the right team members can view synced files?
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Are there recommended workflows for securely handling experiment outputs or logs that may contain sensitive information?
Any advice, best practices, or examples of your workflow would be greatly appreciated!