SECURE INDUSTRIAL IOT DATA AGGREGATION IN THE MANUFACTURING INDUSTRY USING LIGHTWEIGHT HOMOMORPHIC ENCRYPTION SCHEME

Abstract

The rise of the Industrial Internet of Things (IIoT) has revolutionised manufacturing by enhancing efficiency, automation, and data-driven decision-making. However, this advancement presents serious security and privacy challenges, particularly concerning data leaks and unauthorised access. The extensive data sharing among IIoT devices increases their susceptibility to security breaches, which could expose sensitive information and result in financial and physical harm. Moreover, IIoT devices often face resource constraints, such as limited computational power, memory, and battery life, which complicates the implementation of robust security measures. This study focuses on data leakage, unauthorised access, and cyber risks to examine the security issues inherent in IIoT systems. Additionally, it also examined the effect of resource constraints and privacy concerns on the integration of IIoT with Industry 4.0. Recent studies have proposed various solutions to enhance data security and integrity, including homomorphic encryption and blockchain frameworks. In response, this study proposed a novel lightweight homomorphic encryption scheme to address critical vulnerabilities and improve overall security in industrial systems. The encryption scheme was designed and rigorously tested as part of this approach, with findings demonstrating significant improvements in data privacy and system efficiency. The results underscore the importance of robust security measures to ensure the safe and reliable operation of IIoT systems.