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Article detail · 2024

Cybersecurity in a Scalable Smart City Framework Using Blockchain and Federated Learning for Internet of Things (IoT)

Journal

Smart Cities
OpenAlex Open access · gold SJR Q1 JCR Q1 Citations 52 Top 1% Percentile 99.7% FWCI 32.42
Year
2024
DOI
10.3390/smartcities7050109
Type
article

Data source split

  • YÖKSİS venue Smart Cities
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

OpenAlex record

Abstract

OpenAlex · English

Smart cities increasingly rely on the Internet of Things (IoT) to enhance infrastructure and public services. However, many existing IoT frameworks face challenges related to security, privacy, scalability, efficiency, and low latency. This paper introduces the Blockchain and Federated Learning for IoT (BFLIoT) framework as a solution to these issues. In the proposed method, the framework first collects real-time data, such as traffic flow and environmental conditions, then normalizes, encrypts, and securely stores it on a blockchain to ensure tamper-proof data management. In the second phase, the Data Authorization Center (DAC) uses advanced cryptographic techniques to manage secure data access and control through key generation. Additionally, edge computing devices process data locally, reducing the load on central servers, while federated learning enables distributed model training, ensuring data privacy. This approach provides a scalable, secure, efficient, and low-latency solution for IoT applications in smart cities. A comprehensive security proof demonstrates BFLIoT’s resilience against advanced cyber threats, while performance simulations validate its effectiveness, showing significant improvements in throughput, reliability, energy efficiency, and reduced delay for smart city applications.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

52 citations

OpenAlex cited_by_count (cache / database)

14 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. A Probabilistic Approach to Load Balancing in Multi-Cloud Environments via Machine Learning and Optimization Algorithms 2025 Citations 25 · OpenAlex
  2. A Probabilistic Approach to Load Balancing in Multi-Cloud Environments via Machine Learning and Optimization Algorithms 2025 Citations 25 · OpenAlex
  3. A Probabilistic Approach to Load Balancing in Multi-Cloud Environments via Machine Learning and Optimization Algorithms 2025 Citations 25 · OpenAlex
  4. Intelligent Congestion Control in Wireless Sensor Networks (WSN) Based on Generative Adversarial Networks (GANs) and Optimization Algorithms 2025 Citations 19 · OpenAlex
  5. Intelligent Congestion Control in Wireless Sensor Networks (WSN) Based on Generative Adversarial Networks (GANs) and Optimization Algorithms 2025 Citations 19 · OpenAlex
  6. Intelligent Congestion Control in Wireless Sensor Networks (WSN) Based on Generative Adversarial Networks (GANs) and Optimization Algorithms 2025 Citations 19 · OpenAlex
  7. A comprehensive survey of cybersecurity techniques based on quality of service (QoS) on the Internet of Things (IoT) 2025 Citations 18 · OpenAlex
  8. SSLA: a semi-supervised framework for real-time injection detection and anomaly monitoring in cloud-based web applications with real-world implementation and evaluation 2025 Citations 15 · OpenAlex
  9. SSLA: a semi-supervised framework for real-time injection detection and anomaly monitoring in cloud-based web applications with real-world implementation and evaluation 2025 Citations 15 · OpenAlex
  10. Cache Aging with Learning (CAL): A Freshness-Based Data Caching Method for Information-Centric Networking on the Internet of Things (IoT) 2025 Citations 12 · OpenAlex

Authors

No author information.