Affiliation:
1. Shandong University, China
Abstract
Data Migration (DM) is a significant event for an organization in the revolution of Internet of Things (IoT) and Smart City. The total service providers augmented dramatically since, the data generation through IoT in cloud is enormous. Furthermore, the cloud is turning out to be the tools of option for additional cloud storage services along IoT for Smart city. Nevertheless, as more private information/data is transferred to the cloud via social media sites like Baidu WangPan, DropBox, etc., data security and also the privacy issues are questioned. To beat such drawbacks, this paper proposed a security enhancement for the DM system over the cloud environment for Smart City. This work is partitioned into ‘2’ phases where Phase I is a storage phase and Phase II is a retrieval phase. In the storage phase, the data is compressed using MHA and then the data is encrypted utilizing MHECC algorithm for securing data for Smart City. Subsequently, some of the data-related features are extracted. After feature extraction (FE), the distributed cloud server is selected using MGWO. Then, DM is performed dynamically on various cloud servers (CS) using ANFIS. The retrieval phase is the opposite process of the storage phase. In the retrieval phase, the data is decrypted using the same MHECC algorithm and then, the decrypted data is decompressed utilizing the same MHA algorithm. After that, row transposition is performed on both component A and component B. Finally, the components are summed up, and the original data is obtained. Experimental results contrasted the proposed and the prevailing systems centered on key generation time, encryption time, decryption time, security, and threshold.
Publisher
IJAICT India Publications
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