Securing the Internet of Things: Cybersecurity Challenges for Smart Materials and Big Data

Abstract

The Internet of Things (IoT) is transforming society by integrating physical devices, sensors, and data. However, this also introduces cybersecurity vulnerabilities. Intelligent materials and big data analytics are integral emerging technologies within the IoT landscape and bring unique security risks. This extensive research article comprehensively analyses the cybersecurity challenges associated with intelligent materials and big data in the IoT ecosystem. It explores the limitations of innovative materials in terms of computational resources, communication protocols, firmware updates, supply chain integrity, and susceptibility to physical tampering that could lead to privacy, safety, and operational security issues. Furthermore, it examines the data-related risks of breaches, manipulation, unreliable analytics, and tracing data provenance. Next, it provides an in-depth overview of existing and potential cybersecurity solutions tailored for intelligent materials and big data, including blockchain, differential privacy, secure enclaves, and intrusion detection systems. A detailed risk management framework is proposed for building secure, intelligent, material-enabled, and data-driven IoT systems. Best practices are suggested across the lifecycle, including threat modelling, system architecture, product design, data governance, access control, monitoring, incident response, and recovery strategies. Recent case studies of real-world attacks are analysed to highlight salient lessons. In summary, this article aims to provide a comprehensive reference for engineering, business, and policy stakeholders on navigating the pressing cybersecurity challenges in this domain, stimulating further research, and guiding the development of robust IoT ecosystems.