Securing edge based smart city networks with software defined Networking and zero trust architecture

Smart cities are rapidly evolving by adopting Internet of Things (IoT) devices, edge and cloud computing, and mobile connectivity. While these advancements enhance urban efficiency and connectivity, they also significantly increase the risk of cyber threats targeting critical infrastructure. Modern interdependent systems require flexible resilience, allowing them to adapt to changing conditions while maintaining core functions. Smart city networks, however, face unique security vulnerabilities due to their scale and heterogeneity. Altered to industry expectations and requirements, traditional security models are generally restrictive. With its "never trust, always verify' motto, the Zero Trust (ZT) security model starkly differs from traditional models. ZT builds on network design by mandating real time identity verification, giving minimum access permission and mandating respect for the principle of least privilege. Software Defined Networking (SDN) extends one step further by offering central control over the network, policy based autonomous application and immediate response to anomalies. To address these challenges, our proposed Trust-based Resilient Edge Networks (TREN) framework integrates ZT principles to enhance smart city security. Under the umbrella of SDN controllers, SPP, the underpinning component of TREN, performs real time trust analysis and autonomous policy enforcement, for instance, applying high level threat defense mechanisms. TREN dynamically defends against advanced threats like DDoS and Sybil attacks by isolating malicious nodes and adapting defense tactics based on real-time trust and traffic analysis. Trust analysis and policy control modules provide dynamic adaptive coverage, permitting effective proactive defense. Mininet-based simulations demonstrate TREN's efficacy, achieving 95 % detection accuracy, a 20 % latency reduction, and a 25 % increase in data throughput when compared to baseline models.