TY - GEN
T1 - Secure data exchange
T2 - 10th ACM SIGSAC Conference on Cloud Computing Security Workshop, CCSW 2019, co-located with the 26th ACM Conference on Computer and Communications Security, CCS 2019
AU - Gilad-Bachrach, Ran
AU - Laine, Kim
AU - Lauter, Kristin
AU - Rindal, Peter
AU - Rosulek, Mike
N1 - Publisher Copyright: © 2019 Copyright held by the owner/author(s).
PY - 2019/11/11
Y1 - 2019/11/11
N2 - A vast amount of data belonging to companies and individuals is currently stored in the cloud in encrypted form by trustworthy service providers such as Microsoft, Amazon, and Google. Unfortunately, the only way for the cloud to use the data in computations is to first decrypt it, then compute on it, and finally re-encrypt it, resulting in a problematic trade-off between value/utility and security. At a high level, our goal in this paper is to present a general and practical cryptographic solution to this dilemma. More precisely, we describe a scenario that we call Secure Data Exchange (SDE), where several data owners are storing private encrypted data in a semi-honest non-colluding cloud, and an evaluator (a third party) wishes to engage in a secure function evaluation on the data belonging to some subset of the data owners. We require that none of the parties involved learns anything beyond what they already know and what is revealed by the function, even when the parties (except the cloud) are active malicious. We also recognize the ubiquity of scenarios where the lack of an eficient SDE protocol prevents for example business transactions, research collaborations, or mutually beneficial computations on aggregated private data from taking place, and discuss several such scenarios in detail. Our main result is an eficient and practical protocol for enabling SDE using Secure Multi-Party Computation (MPC) in a novel adaptation of the server-aided setting. We also present the details of an implementation along with performance numbers.
AB - A vast amount of data belonging to companies and individuals is currently stored in the cloud in encrypted form by trustworthy service providers such as Microsoft, Amazon, and Google. Unfortunately, the only way for the cloud to use the data in computations is to first decrypt it, then compute on it, and finally re-encrypt it, resulting in a problematic trade-off between value/utility and security. At a high level, our goal in this paper is to present a general and practical cryptographic solution to this dilemma. More precisely, we describe a scenario that we call Secure Data Exchange (SDE), where several data owners are storing private encrypted data in a semi-honest non-colluding cloud, and an evaluator (a third party) wishes to engage in a secure function evaluation on the data belonging to some subset of the data owners. We require that none of the parties involved learns anything beyond what they already know and what is revealed by the function, even when the parties (except the cloud) are active malicious. We also recognize the ubiquity of scenarios where the lack of an eficient SDE protocol prevents for example business transactions, research collaborations, or mutually beneficial computations on aggregated private data from taking place, and discuss several such scenarios in detail. Our main result is an eficient and practical protocol for enabling SDE using Secure Multi-Party Computation (MPC) in a novel adaptation of the server-aided setting. We also present the details of an implementation along with performance numbers.
KW - Cloud computation
KW - Secure multi-party computation
UR - http://www.scopus.com/inward/record.url?scp=85076097842&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/3338466.3358924
DO - https://doi.org/10.1145/3338466.3358924
M3 - منشور من مؤتمر
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 117
EP - 128
BT - CCSW 2019 - Proceedings of the 2019 ACM SIGSAC Conference on Cloud Computing Security Workshop
Y2 - 11 November 2019
ER -