Data anonymization
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This document discusses data anonymization, which is the process of modifying data to prevent individuals from being identified. It describes how data can be anonymized by choosing which attributes like name, address, and phone number to anonymize or whitelist. The document also mentions challenges like dealing with foreign key and unique constraints and provides alternatives to data anonymization like k-anonymity, l-diversity, and t-closeness models as well as other anonymization tools.
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Data anonymization
- 3. Why do we need data?
- 4. What is data anonymization?
- 8. How do we anonymize data?
- 10. You choose which attributes to anonymize ! ! first name last name address zipcode handphone birth date ! ! : Satyam : Agarwala : 87B Amoy Street : 069906 : 8765 4321 : 01/01/1945 BLACKLIST
- 11. WHITELIST You choose which attributes NOT to anonymize ! ! first name last name address zipcode handphone birth date ! ! : Satyam : Woodward : 10 Downing Street : 123456 : 8765 4321 : 01/01/1945
- 12. Show me!
- 13. Script (DSL, strategies, parallelization) ORM (RDBMS, NoSQL) source DB destination DB SUMMARY
- 14. GOTCHAS FK CONSTRAINTS Disable foreign key checks globally before running the script. ! UNIQUE CONSTRAINTS Whitelist or ensure a sequential non-random strategy for attributes that need to be unique.
- 15. Are there other ways to anonymize data?
- 18. THANK YOU!