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.
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The authors would like to thank Logan Praznik for his efforts proofreading and editing this manuscript.
The APC was funded by Yuntao Duan.
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Duan, Y., Li, J., Srivastava, G. et al. Data storage security for the Internet of Things. J Supercomput (2020). https://doi.org/10.1007/s11227-020-03148-7
- Big data
- Database design
- Double secret key
- Deep learning
- Internet of Things
- Data storage security