Trust-Enhanced Lightweight Security Framework for Resource-Constrained Intelligent IoT Systems

Abstract

The prompt expansion of IoT devices necessitates advanced security frameworks to protect data integrity, confidentiality, and availability in resource-constrained environments. Traditional security solutions are often resource-intensive for IoT devices with limited computational power and energy resources. This study addresses these inadequacies by proposing a novel approach formulated to such constraints. This study propose the Trust-Enhanced Lightweight Security Framework (TELSF), integrating two novel components: the Adaptive Lightweight Encryption Algorithm (ALEA) and the Trust-Aware Data Protection Model (TADPM). ALEA employs dynamic key generation through a lightweight hash function, ensuring unique and regularly updated encryption keys based on device context and behavior. TADPM enhances this framework by continuously assessing device trustworthiness through direct interactions, aggregated feedback from neighboring devices, and contextual parameters such as location and device capabilities. Performance evaluations demonstrate that TELSF significantly enhances security and operational efficiency, reducing computational overhead by 18%, improving energy efficiency by 20%, and increasing data transmission security by 10% compared to existing solutions.