ADAPTIVE AND SCALABLE SECURITY FRAMEWORKS FOR FOG-ENABLED SMART CITIES: THREATS, SOLUTIONS AND RESEARCH CHALLENGES
DOI:
https://doi.org/10.5281/zenodo.23015966Keywords:
Fog Computing, Smart Cities, Cyber Security, Intrusion Detection, Blockchain Security, Edge IntelligenceAbstract
Fog computing is a promising paradigm to make real-time data analytics as well as smart services in smart cities. Fog computing expands on computing andstorage resources to the edge of Internet of Things (IoT) devices to reduce latency, alleviate bandwidth issues and improve responsiveness. However, the distributed and heterogeneous nature of fog computing systems introduces a range of security challenges that may affect data privacy, availability and service continuity. This article offers a review of the challenges and solutions for security in fog computing-based smart cities. The study explores existing approaches including blockchain-based secure communication, artificial intelligence-based intrusion detection, lightweight cryptographic algorithms and trust management to evaluate their effects on security threats. It also evaluates recent fog computing models in terms of performance metrics such as latency, throughput, energy and security. Additionally, this study identifies key research challenges and highlights future scope, including the development of adaptive and energy-efficient security mechanisms, explainable AI-based threat detection, and privacy-preserving federated learning models. The study concludes that designing integrated and scalable security frameworks is essential for ensuring the reliability and sustainability of next-generation fog-enabled smart city applications.
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