Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

HUCDO: A Hybrid User-centric Data Outsourcing Scheme

Huang, K., Zhang, X., Wang, X., Mu, Y., Rezaeibagha, F., Xu, G., Wang, H., Zheng, X., Yang, G., Xia, Q. and Du, X. (2020) HUCDO: A Hybrid User-centric Data Outsourcing Scheme. ACM Transactions on Cyber-Physical Systems, 4 (3). pp. 1-23.

Free to read: https://doi.org/10.1145/3379464
*No subscription required

Abstract

Outsourcing helps relocate data from the cyber-physical system (CPS) for efficient storage at low cost. Current server-based outsourcing mainly focuses on the benefits of servers. This cannot attract users well, as their security, efficiency, and economy are not guaranteed. To solve with this issue, a hybrid outsourcing model that exploits both cloud server and edge devices to store data is needed. Meanwhile, the requirements of security and efficiency are different under specific scenarios. There is a lack of a comprehensive solution that considers all of the above issues. In this work, we overcome the above issues by proposing the first hybrid user-centric data outsourcing (HUCDO) scheme. It allows users to outsource data securely, efficiently, and economically via different CPSs. Brielly, our contributions consist of theories, implementations, and evaluations. Our theories include the first homomorphic collision-resistant chameleon hash (HCCH) and homomorphic designated-receiver signcryption (HDRS). As implementations, we instantiate how to use our proposals to outsource small- or large-scale data through distinct CPS, respectively. Additionally, a blockchain with proof-of-discrete-logarithm (B-PoDL) is instantiated to help improve our performance. Last, as demonstrated by our evaluations, our proposals are secure, efficient, and economic for users to implement while outsourcing their data via CPSs.

Item Type: Journal Article
Murdoch Affiliation: Information Technology, Mathematics and Statistics
Publisher: ACM Digital Library
Copyright: © 2020 ACM
URI: http://researchrepository.murdoch.edu.au/id/eprint/56241
Item Control Page Item Control Page