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article · Information Security Journal A Global Perspective

A secure and transparent communication mechanism based on blockchain and fuzzy evaluation matrix in metaverse industry 4.0

Abstract

Recently, Metaverse is gaining prominence within the field of radiology due to its potential to revolutionize image visualization. Radiologists can harness its capabilities to access dynamic, highly detailed results, thereby enhancing diagnostic precision. Digital twins, at the core of the Metaverse, are digital replicas of real-world objects and entities. They serve as the foundational building blocks, enabling the creation of virtual counterparts for everything within the Metaverse. To ensure the reliability of these digital twins, blockchain technology offers a multi-dimensional data storage solution, reinforcing data integrity and trustworthiness. It is used to ensure a transparent and 3D visualization of each communication and interaction for further looking up any criticality if present in the network. With the rapid increase in value and volume of data, the evolution of the metaverse faces a number of privacy and security concerns. Furthermore, the metaverse in Industry 4.0 is a trending topic that further needs to focus on its security challenges at its initial stage. Fortunately, blockchain is considered as one of the significant solutions. The aim of this paper is to propose a secure and efficient fuzzy evaluation matrix by computing the trust values along with integrating with blockchain mechanism in industry 4.0 enabling metaverse environment. The proposed mechanism is validated against various security concerns such as broken authentication, eavesdropping, personal information leakage, data injection, and unauthorized access. The proposed mechanism showed the validation rate against existing schemes with an improvement of 94% in comparison of several security metrics.

Research topics

  • Blockchain Technology Applications and Security
  • Virtual Reality Applications and Impacts
  • Visual Attention and Saliency Detection

Sustainable Development Goals

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DOI: 10.1080/19393555.2024.2353067

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