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BlockEdge: A Privacy-Aware Secured Edge Computing Framework Using Blockchain for Industry 4.0.
1Department of Internet of Things, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, India.
This study introduces a decentralized blockchain approach for edge computing authentication, enhancing security and scalability. The new method eliminates single points of failure and streamlines user access in edge environments.
Area of Science:
- Computer Science
- Cybersecurity
- Distributed Systems
Background:
- Edge computing offers numerous benefits but faces significant data privacy and security challenges.
- Existing authentication methods rely on a single trusted entity, leading to single points of failure and scalability issues.
- Preventing intruder attacks and ensuring only authentic users access data storage are critical in edge environments.
Purpose of the Study:
- To address the limitations of centralized authentication in edge computing.
- To propose a decentralized authentication framework for edge computing using blockchain technology.
- To enhance data privacy, security, and system scalability in edge computing environments.
Main Methods:
- Implementation of a decentralized approach by integrating a blockchain paradigm into edge computing.
- Development of an automated authentication process that eliminates manual registration for users and servers.
- Evaluation of the proposed architecture through experimental results and performance analysis.
Main Results:
- The proposed decentralized architecture effectively eliminates the need for a single trusted entity.
- The blockchain-based authentication scheme ensures automatic and secure access for users and servers.
- Experimental analysis demonstrates superior performance compared to existing authentication methods in edge computing.
Conclusions:
- The decentralized blockchain approach offers a robust solution to edge computing's authentication and security challenges.
- This novel architecture significantly improves system reliability and scalability by removing single points of failure.
- The findings confirm the practical benefits and enhanced performance of the proposed method in edge computing domains.
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