Systematic Analysis of Artificial Intelligence-Driven Trust-based Authentication Schemes for Wireless Sensor Networks

¹ Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, India
² Master of Computer Applications, Ballari Institute of Technology and Management, Ballari, India
³ Department of Computer Science and Engineering, Ballari Institute of Technology and Management, Ballari, India
⁴ Department of Information Science and Engineering, SJB Institute of Technology, Bengaluru, India
⁵ Department of Artificial Intelligence and Machine Learning, SJB Institute of Technology, Bengaluru, India

^* Corresponding author: rajesh-ise@dsatm.edu.in

Abstract

Wireless Sensor Network (WSN) is a system of distributed, autonomous sensors thatare used to monitor the environmental and physical conditions, like sound, pressure, and temperature, and share the information over a network to the sink nodes or a central location.As the data is exchanged over an insecure channel, they are vulnerable to various attacks or manipulations, and hence,network security plays a significant part in the WSN. Thus, a secure authentication protocol is essential to avoid security issues in WSNs. Moreover, the authentication process verifies and identifies devices, like users and nodes, before transmitting the data. This survey presents a review of the varioustrust-based authentication schemes in WSN. Further,the approaches are categorized as Deep Learning (DL) models, Cryptography frameworks, Multifactor authentication techniques, and other modelsare assessed to identify their ability to optimize network security. The articles analyze the papers published between 2018 and 2025, focusing on research methods, the efficiency of the proposed models, performance assessments, and publication years. Additionally, the assessment offers valuable insights for incorporating new techniques to enhance efficiency in trust-based authentication schemes for WSNs.