Quality of Service aware secure data transmission model for Internet of Things assisted wireless sensor networks

Wireless sensor networks (WSNs) are the most critical networks in developing various Internet of Things (IoT) based applications. However, such intelligent devices have drawbacks for energy, memory, processing, and computation resources. In addition, achieving Quality of Service (QoS) with secure data transmission (DT) is a significant challenge for WSNs. This article proposes efficient IoT authentication and energy-aware safe DT models for achieving better QoS and security with lower energy consumption (EC) in WSNs. Initially, the network randomly deploys the sensor nodes (SNs) and performs the registration of the SNs with the base station (BS). Second, the Entropy-based Jaccard similarity induced fuzzy C-means clustering (EJS-FCM) model clusters the SNs based on the intrinsic qualities of nodes. Then the boosted grasshopper optimization algorithm (BGOA) selects the cluster heads (CHs) optimally by considering major fitness parameters such as communication distance, energy, and distance centroid. Following that, an Adler-32 hashing-based authentication scheme performs authentication of every IoT node deployed in the network to provide safer DT. After successful authentication, secure hash elliptical curve cryptography (SHECC) encrypts the data collected from the CHs by incorporating a hashing function both in encryption and decryption, enhancing the IoT data's security level. Finally, in a cloud server (CS), the decentralized blockchain (BC) stores the encrypted data and the authentication credentials of the IoT devices from the BS, which provide additional security to the network. The results of the presented model show its performance efficiency over existing approaches for energy efficiency (EE), QoS, and security.