Lightweight Cryptographic Framework for Securing IoT Devices in Edge Environments

Abstract

The connection of IoT devices to edge computing environments brings significant advantages like cut latency and more real-time processing, as well as reduced bandwidth to increase. However, this distributed and resource-poor environment brings great security risks that traditional cryptanalysis techniques fail to turn into effective solutions. The feasibility of LCF to secure IoT devices operating in the edge scenarios is validated. The suggested structure and method use a joint safety model including an abbreviated round advertisement (L-AES) for fastest and superior in the world encryption, elliptic curve cryptography (ECC) for lightweight and secure key dimension and educating and an outline exertion taken system ensure all around data honesty and legitimacy. Extensive performance evaluation results show that the framework dramatically reduce the computation time, memory utilization, and energy consumption as well as, robust security. Moreover, the information of the system's effectiveness in aiding real-time anomaly detection in edge-IoT environments can be provided by classification-based validation via confusion matrix and ROC-AUC analysis. The results validate that the LCF is suitable for the deployment in scalable, secure, and energy-efficient edge-enables IoT infrastructures.