<p>Fog computing emerges as a pivotal enhancement to cloud computing capabilities, bringing it closer to the data source, thereby reducing latency, bandwidth consumption, and response times while also enhancing security measures. However, due to the decentralized nature of fog computing, security vulnerabilities such as physical attacks, unauthorized access, and lack of trust between fog nodes remain significant challenges. Moreover, existing approaches primarily rely on static trust evaluations, lacking adaptability to real-time security threats and dynamic network conditions. To address these challenges, the study proposes <i>TrustFog</i>, a blockchain-enhanced Bayesian trust model explicitly designed for secure and efficient task scheduling in latency-critical fog computing environments. The proposed <i>TrustFog</i> employs blockchain technology integrated with Proof-of-Authority (PoA) consensus for immutable data integrity while dynamically assessing node trustworthiness through Bayesian networks. Further, the model is implemented on iFogSim2 and validated against established blockchain-based scheduling methods, e.g., BPCRP-FC and BSKM-FC. The results demonstrated <i>TrustFog</i> substantial improvements over existing frameworks, achieving notable performance enhancements including a 65.35% reduction in latency, a 10.4% increase in transaction throughput, and a 93.7% accuracy rate in malicious node detection. Hence, these significant enhancements in both performance and security metrics suggest that <i>TrustFog</i> is a viable solution for latency-sensitive, secure task scheduling in real-world IoT and smart city scenarios.</p>

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Blockchain-enhanced security and bayesian trust assessment for secure task scheduling in latency-critical fog computing environments

  • Navjeet Kaur,
  • Ayush Mittal,
  • Anuj Jain,
  • Umesh Kumar Lilhore,
  • Sultan M. Aldossary,
  • Sarita Simaiya,
  • Ehab Seif Ghith,
  • Abdullah Baihan,
  • Hanaa A. Abdallah,
  • MD Monish Khan

摘要

Fog computing emerges as a pivotal enhancement to cloud computing capabilities, bringing it closer to the data source, thereby reducing latency, bandwidth consumption, and response times while also enhancing security measures. However, due to the decentralized nature of fog computing, security vulnerabilities such as physical attacks, unauthorized access, and lack of trust between fog nodes remain significant challenges. Moreover, existing approaches primarily rely on static trust evaluations, lacking adaptability to real-time security threats and dynamic network conditions. To address these challenges, the study proposes TrustFog, a blockchain-enhanced Bayesian trust model explicitly designed for secure and efficient task scheduling in latency-critical fog computing environments. The proposed TrustFog employs blockchain technology integrated with Proof-of-Authority (PoA) consensus for immutable data integrity while dynamically assessing node trustworthiness through Bayesian networks. Further, the model is implemented on iFogSim2 and validated against established blockchain-based scheduling methods, e.g., BPCRP-FC and BSKM-FC. The results demonstrated TrustFog substantial improvements over existing frameworks, achieving notable performance enhancements including a 65.35% reduction in latency, a 10.4% increase in transaction throughput, and a 93.7% accuracy rate in malicious node detection. Hence, these significant enhancements in both performance and security metrics suggest that TrustFog is a viable solution for latency-sensitive, secure task scheduling in real-world IoT and smart city scenarios.