The system allows users to anonymize any transactional dataset securely by uploading a CSV file. It targets scenarios like healthcare records, e-commerce data, and user activity logs, where sensitive attributes must be hidden not only by identity but also by distribution. The model demonstrates applicability in academic research, commercial dataset publishing, and privacy-preserving machine learning.
-
Notifications
You must be signed in to change notification settings - Fork 0
arwazkhan189/Datashield
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
DataShield – KMT Anonymity App