Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

VD-PSI : verifiable delegated private set intersection on outsourced private datasets

Abadi, Aydin and Terzis, Sotirios and Dong, Changyu (2016) VD-PSI : verifiable delegated private set intersection on outsourced private datasets. In: Financial Cryptography and Data Security. Lecture Notes in Computer Science, 9603 . Springer-Verlag Berlin, Berlin Heidelberg, pp. 149-168. ISBN 978-3-662-54969-8

[img]
Preview
Text (Abadi-etal-FC16-2016-VD-PSI-verifiable-delegated-private-set-intersection-on-outsourced)
Abadi_etal_FC16_2016_VD_PSI_verifiable_delegated_private_set_intersection_on_outsourced.pdf - Accepted Author Manuscript

Download (465kB) | Preview

Abstract

Private set intersection (PSI) protocols have many real world applications. With the emergence of cloud computing the need arises for PSI protocols on outsourced datasets where the computation is delegated to the cloud. However, due to the possibility of cloud misbehaviors, it is essential to verify the correctness of any delegated computation, and the integrity of any outsourced datasets. Verifiable Computation on private datasets that does not leak any information about the data is very challenging, especially when the datasets are outsourced independently by different clients. In this paper we present VD-PSI, a protocol that allows multiple clients to outsource their private datasets and delegate computation of set intersection to the cloud, while being able to verify the correctness of the result. Clients can independently prepare and upload their datasets, and with their agreement can verifiably delegate the computation of set intersection an unlimited number of times, without the need to download or maintain a local copy of their data. The protocol ensures that the cloud learns nothing about the datasets and the intersection. VD-PSI is efficient as its verification cost is linear to the intersection cardinality, and its computation and communication costs are linear to the dataset cardinality. Also, we provide a formal security analysis in the standard model.