TY - JOUR
T1 - Data storage security for the Internet of Things
AU - Duan, Yuntao
AU - Li, Jiangdai
AU - Srivastava, Gautam
AU - Yeh, Jyh Haw
N1 - Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - 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.
AB - 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.
KW - Big data
KW - Data storage security
KW - Database design
KW - Deep learning
KW - Double secret key
KW - Encryption
KW - Hadoop
KW - Internet of Things
UR - http://www.scopus.com/inward/record.url?scp=85077705754&partnerID=8YFLogxK
U2 - 10.1007/s11227-020-03148-7
DO - 10.1007/s11227-020-03148-7
M3 - Article
AN - SCOPUS:85077705754
SN - 0920-8542
VL - 76
SP - 8529
EP - 8547
JO - Journal of Supercomputing
JF - Journal of Supercomputing
IS - 11
ER -