Blockchain-based Light-weight Authentication Approach for a Multiple Wireless Sensor Network

Abstract

The Internet of Things (IoT) uses Wireless Sensor Networks (WSNs) to gather data from particular locations. Environmental monitoring, Army, agronomic, disaster risk management, and tracking systems are just a few of the industries that heavily rely on the WSN of the IoT. Wireless Sensor Network (WSN) is the massive number of sensor nodes dispatched to track a large area, where the control strategies are frequently challenging. In order to prepare these networks for the market, sufficient protection requirements for medium- and large-scale WSNs are a challenging and important target to achieve. To ensure its security, node identity authentication is a significant one. So, we proposed a public blockchain-based multi-wireless sensor network verification method through a Light-Weight Authentication Algorithm (LWAA) for IoT which is used to enhance the secure authentication and performance in WSN in a multi-Wireless Sensor Network model. Here, the nodes are separated between access points, group head nodes, and regular nodes indicated by their power variations that are created into a hierarchical model. The  common authentication of nodes in a number of communication scenarios is identified through blockchain. Our cryptography technique enhances the network life span and decreases the computation time efficiently. The evaluated performance in total power consumption, throughput, latency, packet delivery ratio, time computation, and also proved better results in comparison with the existing authentication methods such as ECDSA, EIBAS, ECBR, and AES.

KEYWORDS:

• Authentication algorithm
• Authentication security
• Cryptography
• Light-weight public block chain
• Wireless sensor network

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

R. Anitha

R Anitha obtained her MTech in computer science and engineering from SRM University Chennai, India. She has teaching experience of over 13 years in engineering colleges. She received Master of Computer Applications (MCA), from the University of Madras, Chennai, India, in 2003 and Master of Philosophy (MPhil) in computer science from Vinakya Mission, Chennai, India, in 2009. She earned undergraduate degree from the University of Madras, Chennai, India, in 2000. She got four international publications. Research interest includes wireless sensor networks, mobile adhoc networks & big data. Email: [email protected]

B. R. Tapas Bapu

B R Tapas Bapu obtained PhD in electronics and communication engineering from St Peters Institute of Higher Education and Research Chennai. India. His areas of interest are nonlinear control systems, artificial intelligence, machine learning, and human-computer interaction. He published 31 articles which include four papers in SCIE and 20 in Scopus indexed journal. He is a reviewer for a international journals in Springer and Inderscience publications. His area of research is wireless sensor networks, network security, and image processing. He is also interested in digital electronics, microprocessor and microcontroller, analogue and digital communication, linear integrated circuits, and control systems. He completed BE (ECE) in the year 1997 from National Engineering College, Kovilpatti, Tamilnadu, India, affiliated to Manonmaniam Sundaranar University. He completed ME (Applied Electronics) in the year 2004 from Hindustan College of Engineering, Chennai, affiliated to Anna University, Chennai.