On Massive Data Storage Security in Cloud Computing with RaptorQ codes
Na Zhao, Yu Zhang, Ke Xiong, Tong Liu · 2018
The security is one of the most important issues which the wide applications of cloud computing. In this paper, we propose a new storage architecture to enhance the massive data storage security of cloud computing by using RaptorQ codes, which is able to provide relatively high-level information access, transfer, data availability, integrity, and confidentiality. The architecture can adjust the sector availability, data confidentiality and data integrity flexibly by setting number of storage nodes and amount of data stored by individual nodes parameters. Performance analysis and experimental results show that our presented RaptorQ codes based storage architecture is capable of achieving high sector availability, data confidentiality and data integrity at low storage, computing and communication costs.