Dataset encryption before model learning
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Type: Question :grey_question:
- Dominant language
- C++
- Stars
- 1k
- Forks
- 175
- Avg merge
- 6d 12h
- Merged PRs (30d)
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Description
Hello!
How do I encrypt a dataset before passing it into a dataloader and then sending it into an architecture for training?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by reviewing TenSEAL's tensor encryption workflow and how datasets, dataloaders, and training architectures are connected. Done would require a clear, agreed explanation of whether and how dataset encryption fits this workflow.
Written by the indexing model from the issue text.
Assessment
- Domain
- cryptography, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100