Implementing Blockchain For Enhanced Security In Fog Computing Systems

A simulation-based framework using iFogSim to secure decentralized fog nodes via blockchain consensus and cryptography

Choon Keat Low; Fung Lim; Bee-Sian Tan; Gar Chi Phoon· IEM Journal· 2026· DOI 10.54552/bzddh935

The core problem

Fog computing has emerged as a pivotal paradigm to overcome the limitations of traditional cloud computing by decentralizing data processing and bringing it closer to the data source. This shift, however, introduces significant security challenges, such as data integrity, authentication, and secure communication among distributed fog nodes. Traditional security measures often fall short in addressing these challenges due to the dynamic and decentralized nature of fog computing environments. Blockchain technology, with its decentralized, immutable, and transparent ledger system, presents a promising solution to these security issues. This research investigates the integration of blockchain technology into fog computing systems to enhance their security framework. The study aims to ensure data integrity, prevent unauthorized access, and secure communications within fog computing environments by leveraging the consensus algorithms and cryptographic techniques inherent in blockchain. The primary objectives include assessing current security vulnerabilities in fog computing, developing a customized blockchain-based security framework, and rigorously evaluating its performance through em

Innovation

The simulation results demonstrate that the blockchain-based security framework significantly enhances the security of fog computing systems. Key findings include: - **Data Integrity**: The immutable ledger ensured that data records could not be tampered with. In simulated attack scenarios, the framework detected and prevented 99.8% of unauthorized modifications. - **Authentication**: The cryptographic authentication mechanism reduced unauthorized access attempts by 95% compared to traditional methods. The consensus algorithm effectively verified node identities. - **Secure Communication**: Encrypted communication channels between fog nodes showed a 90% reduction in interception attempts. Latency overhead introduced by blockchain consensus was measured at an average of 15 ms per transaction, which is acceptable for most fog computing applications. - **Performance Metrics**: Throughput remained stable at 500 transactions per second under normal load, with a slight decrease to 450 TPS under high attack scenarios. The framework maintained 99.9% uptime. These results indicate that the integration of blockchain into fog computing can provide robust security without significantly compr

Fog computing has emerged as a pivotal paradigm to overcome the limitations of traditional cloud computing by decentralizing data processing and bringing it closer to the data source. This shift, however, introduces significant security challenges, such as data integrity, authentication, and secure communication among distributed fog nodes. Traditional security measures often fall short in addressing these challenges due to the dynamic and decentralized nature of fog computing environments. Blockchain technology, with its decentralized, immutable, and transparent ledger system, presents a promising solution to these security issues. This research investigates the integration of blockchain technology into fog computing systems to enhance their security framework. The study aims to ensure data integrity, prevent unauthorized access, and secure communications within fog computing environments by leveraging the consensus algorithms and cryptographic techniques inherent in blockchain. The primary objectives include assessing current security vulnerabilities in fog computing, developing a customized blockchain-based security framework, and rigorously evaluating its performance through empirical analysis and simulation. The findings are expected to provide actionable insights and recommendations for deploying secure and efficient fog computing architectures, thereby contributing to the broader adoption of blockchain-enhanced fog computing systems in various sectors such as IoT, healthcare, and smart cities.

The research utilizes iFogSim, a simulation toolkit for modeling and simulating fog computing environments, to implement and evaluate the proposed blockchain-based security framework. The methodology involves several key steps:

Why it matters

The study confirms that blockchain technology can effectively address the security challenges inherent in fog computing environments. The decentralized and immutable nature of blockchain ensures data integrity and prevents unauthorized access, while cryptographic techniques secure communications. The use of iFogSim allowed for a realistic evaluation of the framework, bridging the gap between theory and practical implementation. However, the integration introduces some overhead, particularly in terms of latency and computational resources. The consensus algorithms, while secure, require additional processing power and energy, which may be a concern for resource-constrained fog nodes. Future research should explore lightweight consensus mechanisms and optimize the framework for low-power devices. The findings have significant implications for various sectors. In IoT, secure fog computing can enable reliable data processing at the edge, reducing reliance on cloud. In healthcare, it can ensure patient data privacy and integrity. In smart cities, it can secure critical infrastructure communications. Overall, this research advances the field of secure distributed computing and provides actionable insights for deploying blockchain-enhanced fog computing systems. The trade-off between security and performance is quantified by the following relationship: Overhead = α \cdot lo g (n) + β \cdot k where n is the number of nodes, k is the number of consensus rounds, and α, β are constants dependent on the implementation. This suggests that scaling the network increases overhead logarithmically, which is manageable with proper optimization.

Who should read this

CS practitioners and researchers

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