Blockchain enabled authentication system for edge and fog computering

Low-cost IoT sensors are widely used but face significant challenges in data quality, scalability, reliability, and security, particularly in distributed edge and fog computing environments. While edge and fog computing aim to improve device performance and data analytics, they inherit limitations from cloud computing, making this environment vulnerable to attacks. Current authentication methods in these environments often struggle with resource consumption, scalability, and security issues. Existing blockchain-based solutions, such as those using ethereum, have shown promise in addressing some of these challenges. However, they still face limitations in transaction speed, energy efficiency, and scalability when applied to edge and fog computing environments. Furthermore, there is a lack of comprehensive approaches that integrate user-specific data for secure registration and authentication while maintaining efficiency in resource-constrained environments. This research addresses the gaps in edge and fog computing environments and explores the utilisation of blockchain technologies and their application in edge and fog authentication systems. The study focusses on overcoming the scalability and security limitations inherent in current edge and fog computing environments, with potential applications in 6G-enabled IoT environments. By investigating these areas, this research seeks to contribute to the understanding of authentication and privacy in decentralised edge and fog computing environments, potentially providing a framework for leveraging blockchain technologies to improve security, scalability, and efficiency in next-generation computing systems.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-24
DOI
https://doi.org/10.5281/zenodo.15277135
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blockchain enabled authentication system for edge and fog computering

Zenodo (CERN European Organization for Nuclear Research)
IoT and Edge/Fog Computing
article

Blockchain enabled authentication system for edge and fog computering

article en

Abstract

Low-cost IoT sensors are widely used but face significant challenges in data quality, scalability, reliability, and security, particularly in distributed edge and fog computing environments. While edge and fog computing aim to improve device performance and data analytics, they inherit limitations from cloud computing, making this environment vulnerable to attacks. Current authentication methods in these environments often struggle with resource consumption, scalability, and security issues. Existing blockchain-based solutions, such as those using ethereum, have shown promise in addressing some of these challenges. However, they still face limitations in transaction speed, energy efficiency, and scalability when applied to edge and fog computing environments. Furthermore, there is a lack of comprehensive approaches that integrate user-specific data for secure registration and authentication while maintaining efficiency in resource-constrained environments. This research addresses the gaps in edge and fog computing environments and explores the utilisation of blockchain technologies and their application in edge and fog authentication systems. The study focusses on overcoming the scalability and security limitations inherent in current edge and fog computing environments, with potential applications in 6G-enabled IoT environments. By investigating these areas, this research seeks to contribute to the understanding of authentication and privacy in decentralised edge and fog computing environments, potentially providing a framework for leveraging blockchain technologies to improve security, scalability, and efficiency in next-generation computing systems.

Zenodo (CERN European Organization for Nuclear Research)
University of the West of Scotland (GB)
Decent work and economic growth
Openalex Percentile: Top 51%
IoT and Edge/Fog Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.