Data storage security for the Internet of Things
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Data storage security for the Internet of Things Yuntao Duan1 · Jiangdai Li2 · Gautam Srivastava3,4 · Jyh‑Haw Yeh5
© Springer Science+Business Media, LLC, part of Springer Nature 2020
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. Keywords Big data · Database design · Double secret key · Hadoop · Deep learning · Internet of Things · Encryption · Data storage security
1 Introduction Traditional smart devices often need to be replaced and/or have their software upgraded. However, some infrastructures can lay idle and waste resources under reduced load [1, 2]. The proposal of Internet of Things (IoT) was motivated by these shortfalls. Cloud IoT storage means that businesses and individual users alike hand over data and services to third-party service providers [3, 4]. These third parties store, publish and maintain data, which allows users to cut the cost of their own infrastructure [5, 6]. We also saw that the IoT can effectively prevent data loss, * Gautam Srivastava [email protected] Extended author information available on the last page of the article
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equipment damage and weak mobility [7, 8]. With the development of IoT, data storage for IoT platforms has received the attention of relevant experts and scholars throughout the world [9, 10]. Slowly, better methods are proposed for all aspects of IoT. A traditional method of low-cost data storage security and processing framework design under a cloud environment is proposed in [11]. Matrix-based data mining algorithms are studied in depth, with a focus on the secure top-k feature vector algorithm. An iterative processing model is adopted in this algorithm. Authorized users could interact with the cloud directly to obtain the expected results. The source matrix and intermediate results are kept in a confidential state during the interaction. In addition, security for the new alg
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