Blockchain-Enhanced Secure Data-Driven QoS Framework for Wireless Sensor Networks

Abstract

This paper presents the Blockchain-Enhanced Secure Data-Driven Quality of Service (QoS) Framework (BES-DQF) for security and efficiency of wireless sensor networks (WSNs) and Internet of Things (IoT) systems. The framework combines data integrity verification using blockchain, smart contract enforcement, security compliance, and deep learning algorithms for QoS optimization. The novel combination of these technologies ensures that only verified data enters the deep learning model, avoiding adversarial attacks, such as data poisoning and Sybil attacks. Experimental results show that the accuracy of BESDQF in QoS prediction is 94%, and the attack detection rate is 92%, which is better than that of traditional QoS systems, which are only 93% accurate and 61% attack detection. In addition, BES-DQF maintains an acceptable latency overhead (+6.8%) and energy consumption (+5.4%), proving it to be practical for large-scale IoT applications. Our contributions include (1) the development of a secure blockchain-integrated QoS optimization model, (2) the introduction of a novel attack-resistant learning pipeline, and (3) a comprehensive experimental validation to show the superior performance and robustness of BES-DQF in adversarial conditions. Future work will be done on consensus optimization for scalability and federated learning for enhanced privacy and decentralization.