Improving Reliability and Data Management in Internet of Things Based Wireless Sensor Networks

Abstract

ABSTRACT With the rapid growth of the Internet of Things (IoT), wireless sensor networks (WSNs) are becoming increasingly vital in advancing information and communication technologies. These networks are widely integrated with the Internet across numerous applications. In WSN‐assisted IoT, ensuring energy efficiency and security is critical for Quality of Service (QoS), but remains challenging due to the networks' open and resource‐constrained nature. This paper introduces a novel solution: a secure entropy‐based Jaccard similarity integrated with a fuzzy C‐means (EJS‐FCM) clustering approach for dynamic WSN‐IoT networks. Cluster heads (CHs) are selected using a boosted grasshopper optimization (BGO) algorithm, and an Adler‐32 hashing‐based scheme authenticates each sensor node. Secure hash elliptical curve cryptography (SHECC) then encrypts data collected from the CHs, enhancing IoT data security through hashing functions in both encryption and decryption. The proposed approach significantly improves security, QoS, and energy efficiency, as evidenced by enhanced network lifetime, throughput, packet delivery ratio, delay, and encryption time.