Data Security in Industrial IoT: Challenges and Emerging Solutions

Abstract

The implementation of Industrial Internet of Things (IIoT) is significantly constrained by the emergence of Data security. This paper examines the primary data security issues and protection mechanisms associated with IIoT, providing a comprehensive analysis of how security protection systems evolve across the stages of data collection, transmission, storage, and processing. The focus is directed towards advancements in edge computing and lightweight distributed ledger technologies, which significantly enhance data security. The paper begins with a review of the evolution and development of IIoT, highlighting the challenges that current technologies present in effectively addressing data privacy, integrity, real-time performance, and scalability. Following this, the analysis focuses on the efficacy of edge computing to mitigate data exposure while simultaneously improving computational efficiency. Additionally, the study examines the benefits of lightweight distributed ledger technologies for resource-constrained environments, highlighting their role in ensuring data immutability and enhancing data transparency. The paper concludes by analyzing potential trends in IIoT data security technologies, such as post-quantum cryptography, AI-driven security protections, and zero-trust architectures, and by offering perspectives on the future of technological advancements.