Trust-Aware Hierarchical Clustering for Secure Energy Optimization in Smart Health Sensor Networks
Аннотация
Smart Health Sensor Networks (SHSNs) are pivotal in real-time health monitoring, enabling the continuous collection and transmission of sensitive physiological data. To ensure reliability and longevity in such systems, both security and energy efficiency must be optimized. Existing clustering methods often lack robust trust evaluation mechanisms, making them vulnerable to malicious nodes and leading to rapid energy depletion and compromised data integrity. To address these limitations, this paper introduces a novel Trust-aware Secure Energy Optimization Framework (TSEOF) that integrates trust evaluation with hierarchical clustering. The proposed TSEOF dynamically assesses the trustworthiness of nodes based on behavioral metrics and incorporates this trust score into the clustering process to isolate unreliable nodes. This approach enhances network longevity and data accuracy by selecting only trustworthy and energy-efficient nodes as cluster heads. Simulation results demonstrate that TSEOF significantly improves energy efficiency, reduces data loss due to malicious activities, and extends the overall network lifetime compared to traditional methods. The framework ensures secure communication with minimal computational overhead, making it ideal for real-time health monitoring applications.