Research on Secure Storage Technology of Spatiotemporal Big Data Based on Blockchain

Author:

Zhou Bao1234,Zhao Junsan1234,Chen Guoping1234,Yin Ying5

Affiliation:

1. Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China

2. Key Laboratory of Geospatial Information Integration Innovation for Smart Mines, Kunming 650093, China

3. Spatial Information Integration Technology of Natural Resources in Universities of Yunnan Province, Kunming 650211, China

4. The Industry-University-Research Integration Innovation Base of Natural Resources Smart Management, Kunming 650211, China

5. College of Electronic and Information Engineering, West Anhui University, Lu’an 237000, China

Abstract

With the popularity of spatiotemporal big data applications, more and more sensitive data are generated by users, and the sharing and secure storage of spatiotemporal big data are faced with many challenges. In response to these challenges, the present paper puts forward a new technology called CSSoB (Classified Secure Storage Technology over Blockchain) that leverages blockchain technology to enable classified secure storage of spatiotemporal big data. This paper introduces a twofold approach to tackle challenges associated with spatiotemporal big data. First, the paper proposes a strategy to fragment and distribute space–time big data while enabling both encryption and nonencryption operations based on different data types. The sharing of sensitive data is enabled via smart contract technology. Second, CSSoB’s single-node storage performance was assessed under local and local area network (LAN) conditions, and results indicate that the read performance of CSSoB surpasses its write performance. In addition, read and write performance were observed to increase significantly as the file size increased. Finally, the transactions per second (TPS) of CSSoB and the Hadoop Distributed File System (HDFS) were compared under varying thread numbers. In particular, when the thread number was set to 100, CSSoB demonstrated a TPS improvement of 7.8% in comparison with HDFS. Given the remarkable performance of CSSoB, its adoption can not only enhance storage performance, but also improve storage security to a great extent. Moreover, the fragmentation processing technology employed in this study enables secure storage and rapid data querying while greatly improving spatiotemporal data processing capabilities.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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