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Edge computing is transforming smart cities by enabling rapid, local data processing and reducing core network congestion, but decentralization also broadens the attack surface, exposing systems to novel security and privacy threats. Traditional cloud-based defenses often fall short in these dynamic and distributed environments. This paper delivers four main contributions: (1) a unified taxonomy of edge computing threats in smart cities, including data privacy/integrity risks, identity and access vulnerabilities, and emerging AI-driven and physical attacks; (2) a critical comparison of five leading defense strategies, AI-based anomaly detection, blockchain-enabled trust, hardware roots of trust, secure virtualization and privacy-preserving analytics, evaluated for security, overhead and deployment maturity, with practical recommendations; (3) an analysis of the sustainability implications of security solutions, focusing on energy and carbon impacts and their alignment with Sustainable Development Goals (SDGs); and (4) a forward-looking roadmap highlighting challenges such as quantum-resistant cryptography, federated learning, digital twin-based risk modeling, and real-time policy enforcement. Together, these contributions provide a structured framework for designing secure, reliable, and sustainable edge infrastructures in future smart cities.
Mrabet et al. (Wed,) studied this question.