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About this paper
Guy Blanc, William Pires, Toniann Pitassi
Researchers from Stanford and Columbia Universities established that a set of four fundamental axioms for privacy measures implies equivalence to approximate Differential Privacy, formally justifying DP's widespread adoption. This equivalence holds for measures that exhibit properties like strong composition and linear scalability while avoiding basic information leakage.
Key insights
- Any privacy measure satisfying the four specified axioms is functionally equivalent to approximate Differential Privacy, providing a strong theoretical justification for DP's foundational role.
- Algorithmic stability, particularly TV-Stability, serves as a crucial intermediate property, demonstrating a deep connection between robust data analysis and data protection.
- The set of four axioms is minimal; removing any single axiom allows for 'ill-behaved' privacy measures that permit tasks impossible for DP to solve efficiently.
Summary by alphaXiv.
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