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Practical Secure Computation Outsourcing: A Survey
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DOI：10.1145/3158363.png)
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摘要
En 中文
The rapid development of cloud computing promotes a wide deployment of data and computation outsourcing to cloud service providers by resource-limited entities. Based on a pay-per-use model, a client without enough computational power can easily outsource large-scale computational tasks to a cloud. Nonetheless, the issue of security and privacy becomes a major concern when the customer's sensitive or confidential data is not processed in a fully trusted cloud environment. Recently, a number of publications have been proposed to investigate and design specific secure outsourcing schemes for different computational tasks. The aim of this survey is to systemize and present the cutting-edge technologies in this area. It starts by presenting security threats and requirements, followed with other factors that should be considered when constructing secure computation outsourcing schemes. In an organized way, we then dwell on the existing secure outsourcing solutions to different computational tasks such as matrix computations, mathematical optimization, and so on, treating data confidentiality as well as computation integrity. Finally, we provide a discussion of the literature and a list of open challenges in the area.
Keyword:
Cloud Computation
large-scale dataset
data security
privacy preservation
computation integrity
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