Data storage security for the Internet of Things

Yuntao Duan, Jiangdai Li, Gautam Srivastava, Jyh Haw Yeh

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In the present era, secure data storage for any Internet of Things (IoT) platform is plagued by poor performance of secure read and write operations, which limits the use of data storage security on any IoT platform. Therefore, in this paper, a data storage security method based on double secret key encryption and Hadoop suitable for any IoT platform is proposed. First, the Hadoop deep learning architecture and implementation process are analyzed, and the process of client Kerberos identity authentication in the Hadoop framework is discussed. From this, the current shortcomings of data storage security based on the Hadoop framework are analyzed. The elements of data storage security are also determined. Furthermore, a novel double secret key encryption method for data storage security and to improve the security of stored data itself is introduced. Simultaneously, hash computing is used to improve the read and write performance of data after secure storage. Experimental results clearly show that our proposed method can effectively improve read and write performance of data, and that the performance of data security operations is improved from current standard implementations.

Original languageEnglish
Pages (from-to)8529-8547
Number of pages19
JournalJournal of Supercomputing
Volume76
Issue number11
DOIs
StatePublished - 1 Nov 2020

Keywords

  • Big data
  • Data storage security
  • Database design
  • Deep learning
  • Double secret key
  • Encryption
  • Hadoop
  • Internet of Things

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