Jupyter notebooks are a core element in many data science workflows. However, analyzing sensitive data, such as personally identifiable information or health records, presents a security challenge because notebooks are not encrypted at rest.
By extending Jupyter’s FileManager hook, we demonstrate how to transparently increase security and compliance by working directly with encrypted notebooks. The first encryption backend we discuss leverages GPG tools, which works well for individuals and small teams. The second backend uses the encryption-as-a-service feature provided by Vault and is more appropriate for larger teams. We’ll also discuss implications for managing encryption across a typical data science team, including things like managing notebooks version control.
Attendees should leave with simple actionable steps to harden the security of Jupyter notebooks.
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