Distributed Private Data Analysis: Simultaneously Solving How and What

DOI10.1007/978-3-540-85174-5_25zbMath1183.68080OpenAlexW1872473787MaRDI QIDQ3600234

Eran Omri, Amos Beimel, Kobbi Nissim

Publication date: 10 February 2009

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-85174-5_25

Mathematics Subject Classification ID

Distributed systems (68M14) Network protocols (68M12) Authentication, digital signatures and secret sharing (94A62)

Related Items (18)

Limits on the usefulness of random oracles ⋮ Separating Computational and Statistical Differential Privacy in the Client-Server Model ⋮ Efficient noise generation to achieve differential privacy with applications to secure multiparty computation ⋮ Rate-limited secure function evaluation ⋮ Rejoinder ⋮ Comment ⋮ Comment ⋮ Channels of small log-ratio leakage and characterization of two-party differentially private computation ⋮ On differential privacy and adaptive data analysis with bounded space ⋮ Confidential gossip ⋮ Concurrent composition of differential privacy ⋮ Computational Two-Party Correlation: A Dichotomy for Key-Agreement Protocols ⋮ Rate-Limited Secure Function Evaluation: Definitions and Constructions ⋮ Minimax Optimal Procedures for Locally Private Estimation ⋮ Non-interactive anonymous router ⋮ Unnamed Item ⋮ Spreading the privacy blanket: differentially oblivious shuffling for differential privacy ⋮ The Complexity of Differential Privacy

Cites Work

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• A communication-privacy tradeoff for modular addition
• Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
• What Can We Learn Privately?
• Our Data, Ourselves: Privacy Via Distributed Noise Generation
• Advances in Cryptology – CRYPTO 2004
• Theory of Cryptography
• Theory of Cryptography
• Differential Privacy

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