GreenSecure-IoT: An Energy-Efficient Adaptive Authentication Framework for Smart City Edge Networks

Abstrak

The fast deployment of smart city infrastructures and edge-enabled Internet of Things (IoT) environments has posed a considerable wariness in terms of cybersecurity and energy efficiency among resource-constrained devices. Standard as well as standard authentication mechanisms mostly base their functioning on static safety and security configurations that may not adjust proficiently to the vibrant adjustments in risk scenarios, device energy condition, or heterogeneous network environment. In addition, the existing schemes are often constrained by high computational overheads and communication costs, as well as low-resilience against incentive-compatible adaptive attacks for advanced cyber attacks and future quantum threats. To overcome these limitations, this paper proposes Green Secure-IoT, an adaptive energy-efficient authentication framework to secure smart city edge networks. The combination of low-effort authentication, AI-supported threat assessment, decentralized trust management based on reputation systems aided by blockchain-assisted revocation and post-quantum cryptographic defense mechanisms constitutes an overall adaptive cybersecurity framework. In contrast to the static approaches for authentication, GreenSecure-IoT dynamically features an appropriate mode of authentication based on devise’s energy levels, reputation levels, and network attack characteristics by making use of distributed management method. Under low energy conditions lightweight authentication is activated to keep computational overhead exceptionally low, whereas high-security post-quantum CRYSTALS-Kyber / CRYSTALS-Dilithium authenticated encryption (AEAD) is used in hostile threat conditions. The framework described was built upon and analyzed in the context of the ESP32 IoT devices, Raspberry Pi edge gateways, and OMNeT++-based smart city simulations validated based on available Architectural Patterns. The experimental results show that, compared to existing authentication schemes, GreenSecure IoT can greatly reduce the number of communications betweennodes; lower memory efficiency and authentication delay; and much less energy consumption. When combined with the AI-based adaptive security mechanism, it implements malicious behavior detection while being lightweight and computational resource friendly for IoT devices. In conclusion, the GreenSecure-IoT framework proposed in this paper offers a multi-benefit scalable, smart and cyber-aware energy-related cybersecurity solution to further improve long-term security and operational sustainability of next generation smart city edge networks.

Kata kunci

• Smart City Security
• Internet of Things (IoT)
• Edge Computing
• Energy-Efficient Authentication
• Adaptive Security
• Post-Quantum Cryptography (PQC)
• Blockchain-Based Revocation