A Cryptographic Security Mechanism for Dynamic Groups for Public Cloud Environments

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Keywords: Cloud Computing, Cloud Data Security, Dynamic Groups, Homomorphic Encryption, Chaotic Network, Throughput, Avalanche Effect.

Abstract

Cloud computing has emerged as a significant technology domain, primarily due to the emergence of big data, machine learning, and quantum computing applications. While earlier, cloud computing services were focused mainly on providing storage and some infrastructures/platforms for applications, the need to advance computational power analysis of massive datasets. It has made cloud computing almost inevitable from most client-based applications, mobile applications, or web applications. The allied challenge to protect data shared from and to cloud-based platforms has cropped up with the necessity to access public clouds. While conventional cryptographic algorithms have been used for securing and authenticating cloud data, advancements in cryptanalysis and access to faster computation have led to possible threats to the traditional security of cloud mechanisms. This has led to extensive research in homomorphic encryption pertaining to cloud security. In this paper, a security mechanism is designed targeted towards dynamic groups using public clouds. Cloud security mechanisms generally face a significant challenge in terms of overhead, throughput, and execution time to encrypt data from dynamic groups with frequent member addition and removal. A two-stage homomorphic encryption process is proposed for data security in this paper. The performance of the proposed system is evaluated in terms of the salient cryptographic metrics, which are the avalanche effect, throughput, and execution time. A comparative analysis with conventional cryptographic algorithms shows that the proposed system outperforms them regarding the cryptographic performance metrics.

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Published
23.05.2023 — Updated on 25.05.2023
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How to Cite

A Cryptographic Security Mechanism for Dynamic Groups for Public Cloud Environments. (2023). Journal of Automation, Mobile Robotics and Intelligent Systems, 16(2), 46-54. https://doi.org/10.14313/JAMRIS/2-2022/15

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