Taxonomy-Based Lightweight Cryptographic Frameworks for Secure Industrial IoT: A Survey

Manufacturing and automation are undergoing a radical transformation thanks to the advancement of the Industrial Internet of Things (IIoT), which enables real-time tracking, predictive analysis, and interconnected device ecosystems. However, the heterogeneous and massive deployment of devices deprives IIoT systems of a security advantage. Traditional cryptographic methods, while secure, are prohibitively computationally expensive for such settings. Lightweight cryptography models are promising alternatives in terms of providing quality security with low resource consumption. In this paper, we propose a structured classification of lightweight cryptographic frameworks for IIoT depending on the types of algorithms, functional goals, deployment domains, and application domains. Comparisons reveal the computation performance, energy, and memory costs among different methods, and may provide some hints for practitioners to determine the best deployment. In contrast to the previous works, in this paper, we consider the security challenges of the IIoT and derive a layered framework for performance-/application-based selection. Future trend directions highlight the search for post-quantum cryptographic solutions, scalable authentication, and energy-aware hybrid approaches, anchoring this survey as a roadmap for the secure development of IIoT.