Differential Privacy meets Verifiable Computation: Achieving Strong Privacy and Integrity Guarantees

Item Type	Conference or Workshop Item (Paper)
Abstract	Often service providers need to outsource computations on sensitive datasets and subsequently publish statistical results over a population of users. In this setting, service providers want guarantees about the correctness of the computations, while individuals want guarantees that their sensitive information will remain private. Encryption mechanisms are not sufficient to avoid any leakage of information, since querying a database about individuals or requesting summary statistics can lead to leakage of information. Differential privacy addresses the paradox of learning nothing about an individual, while learning useful information about a population. Verifiable computation addresses the challenge of proving the correctness of computations. Although verifiable computation and differential privacy are important tools in this context, their interconnection has received limited attention. In this paper, we address the following question: How can we design a protocol that provides both differential privacy and verifiable computation guarantees for outsourced computations? We formally define the notion of verifiable differentially private computation (VDPC) and what are the minimal requirements needed to achieve VDPC. Furthermore, we propose a protocol that provides verifiable differentially private computation guarantees and discuss its security and privacy properties.
Authors	Tsaloli, Georgia & Mitrokotsa, Aikaterini
Language	English
Subjects	computer science
HSG Classification	contribution to scientific community
Date	2019
Page Range	425-430
Event Title	Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, ICETE 2019 - Volume 2: SECRYPT, Prague, Czech Republic, July 26-28, 2019
Official URL	https://doi.org/10.5220/0007919404250430
Depositing User	Prof. Dr. Katerina Mitrokotsa
Date Deposited	06 Feb 2021 18:59
Last Modified	20 Jul 2022 17:44
URI:	https://www.alexandria.unisg.ch/publications/262273

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Tsaloli, Georgia & Mitrokotsa, Aikaterini: Differential Privacy meets Verifiable Computation: Achieving Strong Privacy and Integrity Guarantees. 2019. - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, ICETE 2019 - Volume 2: SECRYPT, Prague, Czech Republic, July 26-28, 2019.

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https://www.alexandria.unisg.ch/id/eprint/262273

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