A Comparative Study of Secure and Efficient Data Duplication Mechanisms for Cloud-Based IoT Applications

Abstract

Cloud-based processes store enormous amounts of data to support several daily applications, especially in intelligent systems and the Industrial Internet of Things (IIoT) applications. The advancement of hosted cloud storage services endorses the productivity of IIoT applications. It is critical to enabling businesses to increase data security, privacy, efficiency, accessibility, and flexibility. There are many concerns for cloud providers, including storage overhead, upload/download bandwidth, and data security and privacy. Utilizing secure data deduplication technology, cloud service providers may maximize their available storage capacity, resulting in effective and secure disk space use. This review focuses on a comparative study of secure data deduplication mechanisms for cloud-based applications, including MD5 and various versions of SHA. These techniques remove duplicate data in different storage levels and enhance users’ data integrity, confidentiality, and privacy protection. It is computationally more efficient than traditional compression methods, which may support IoT applications to manage the exponential growth of their data. We also present an overview and classification of the most recent research on data deduplication based on essential mechanisms.