Lightweight Zero‐Trust Curve Protocol for Securing Resource‐Constrained Devices in Edge Network

ABSTRACT Securing resource‐constrained edge devices remains a significant challenge due to limited computational capability, restricted energy resources, and the unsuitability of conventional security mechanisms designed for centralized systems. As edge computing increasingly supports latency‐sensitive and mission‐critical applications, existing authentication and encryption approaches often impose high computational overhead, rely on static trust assumptions, or lack adaptive security enforcement. These limitations reduce scalability, increase energy consumption, and hinder reliable deployment in dynamic edge environments. To address these challenges, this study proposes a Lightweight Zero‐Trust Curve Protocol (LZTCP), a unified security framework tailored for resource‐constrained edge networks. The framework integrates a hybrid lightweight cryptographic strategy that combines efficient symmetric encryption with elliptic curve–based secure key exchange to ensure data confidentiality while maintaining low latency and energy efficiency. In addition, an adaptive authentication mechanism based on message authentication codes is employed, where authentication intensity is dynamically adjusted according to device trust scores under a zero‐trust security model. Trust‐aware secure routing is also incorporated to enhance communication reliability by selecting paths based on both efficiency and node trustworthiness. The effectiveness of the proposed framework is validated through extensive simulation‐based performance evaluation. The results demonstrate that LZTCP significantly outperforms existing edge authentication protocols by reducing authentication time by 84.58%, communication delay by 97.77%, energy consumption by 93.31%, and computational cost by 61.75%. These findings confirm that the proposed approach provides strong security guarantees while remaining efficient and practical for latency‐sensitive and energy‐constrained edge computing applications.