Authors:
Radu Ciucanu
1
;
Matthieu Giraud
1
;
Pascal Lafourcade
1
and
Lihua Ye
2
Affiliations:
1
LIMOS, Université Clermont Auvergne, Aubière and France
;
2
Harbin Institute of Technology, Harbin, Weihai, Shenzhen and China
Keyword(s):
Database Queries, MapReduce, Security, Grouping, Aggregation.
Related
Ontology
Subjects/Areas/Topics:
Data and Application Security and Privacy
;
Data Protection
;
Database Security and Privacy
;
Information and Systems Security
;
Security and Privacy for Big Data
;
Security and Privacy in the Cloud
;
Security in Distributed Systems
;
Security in Information Systems
Abstract:
MapReduce programming paradigm allows to process big data sets in parallel on a large cluster. We focus on a scenario where the data owner outsources her data on an honest-but-curious server. Our aim is to evaluate grouping and aggregation with SUM, COUNT, AVG, MIN, and MAX operations for an authorized user. For each of these five operations, we assume that the public cloud provider and the user do not collude i.e., the public cloud does not know the secret key of the user. We prove the security of our approach for each operation.