Abstract
Computation outsourcing is an integral part of cloud computing. It enables end-users to outsource their computational tasks to the cloud and utilize the shared cloud resources in a pay-per-use manner. However, once the tasks are outsourced, the end-users will lose control of their data. To address this problem, secure outsourcing mechanisms have been proposed to ensure security of the end-users outsourced data. In this paper, we investigate outsourcing of general computational problems which constitute the mathematical basics for problems emerged from various fields such as engineering and finance. To be specific, we propose affine mapping based schemes for the problem transformation and outsourcing so that the cloud is unable to learn any key information from the transformed problem. Meanwhile, the overhead for the transformation is limited to an acceptable level compared to the computational savings introduced by the outsourcing itself. Furthermore, we develop cost-aware schemes to balance the trade-offs between end-users various security demands and computational overhead. We also propose a verification scheme to ensure that the end-users will always receive a valid solution from the cloud. Our extensive complexity and security analysis show that our proposed Cost- Aware Secure Outsourcing (CASO) scheme is both practical and effective
Original language | English |
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Journal | IEEE Transactions on Services Computing |
DOIs | |
Publication status | Accepted/In press - 14 Mar 2018 |
Externally published | Yes |
Keywords
- Cloud computing
- computation outsourcing
- cost-awareness
- efficiency
- Linear programming
- Mathematical model
- Outsourcing
- Security
- security
- Servers
- Task analysis
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
- Information Systems and Management