Protecting Data While Maintaining Analyzability & Its Business Value: Is It FACT or FICTION
summary
Claims that data can stay analyzable while protected by labeling and selective transformations, with attackers being external in about 75% of breaches and insiders about 30%. Specific techniques include tokenization that preserves format (keep first six and last four of card numbers) and dynamic masking for views, plus role-based reversal so only ~3–4% of users see full PANs. Built outcome is a policy-driven, data-centric protection layer that preserves sort/filter/aggregate use without redesigning schemas.
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chapters (8)
- 0:00Start
- 3:35A TYPICAL DATA SECURITY APPROACH
- 5:42POTENTIAL ATTRIBUTES FOR PROTECTION
- 6:24APPLYING ZERO TRUST PRINCIPLES TO SENSITIVE DATA
- 7:09USER-CENTRIC APPROACH
- 8:45CHOICE OF PROTECTION METHODS
- 14:27WHAT CAN WE DO TO GIVE TO PROTECTED DATA A BUSINESS VALUE?
- 16:37ROLE-BASED ACCESS CONTROLS
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