Towards a general framework for secure MapReduce computation on hybrid clouds

Authors:
Chunwang Zhang;Ee-Chien Chang;Roland H. C. Yap
Affiliations:
National University of Singapore;National University of Singapore;National University of Singapore
Venue:
Proceedings of the 4th annual Symposium on Cloud Computing
Year:
2013

Citing 4
Cited 0

MapReduce: simplified data processing on large clusters

OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Fully homomorphic encryption using ideal lattices

Proceedings of the forty-first annual ACM symposium on Theory of computing
Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds

Proceedings of the 16th ACM conference on Computer and communications security
Sedic: privacy-aware data intensive computing on hybrid clouds

Proceedings of the 18th ACM conference on Computer and communications security

Quantified Score

Hi-index	0.00

Visualization

Abstract

The idea of a hybrid cloud is to combine a private cloud (e.g., an organization's in-house private datacenter) together with a public cloud (e.g., Amazon EC2). Hybrid cloud computing offers increased scalability and cost-effectiveness: the private cloud can be used for typical workloads, but when additional resources are needed during peak computations, the public cloud is harnessed. This hybrid cloud architecture has already gained adoption [1] and is still undergoing rapid development [4].