An AI-Driven Framework for Integrated Security and Privacy in Internet of Things Using Quantum-Resistant Blockchain

Mahmoud Elkhodr ()
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Mahmoud Elkhodr: College of Computer Engineering and Science, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi Arabia

Future Internet, 2025, vol. 17, issue 6, 1-22

Abstract: The growing deployment of the Internet of Things (IoT) across various sectors introduces significant security and privacy challenges. Although numerous individual solutions exist, comprehensive frameworks that effectively combine advanced technologies to address evolving threats are lacking. This paper presents the Integrated Adaptive Security Framework for IoT (IASF-IoT), which integrates artificial intelligence, blockchain technology, and quantum-resistant cryptography into a unified solution tailored for IoT environments. Central to the framework is an adaptive AI-driven security orchestration mechanism, complemented by blockchain-based identity management, lightweight quantum-resistant protocols, and Digital Twins to predict and proactively mitigate threats. A theoretical performance model and large-scale simulation involving 1000 heterogeneous IoT devices were used to evaluate the framework. Results showed that IASF-IoT achieved detection accuracy between 85% and 99%, with simulated energy consumption remaining below 1.5 mAh per day and response times averaging around 2 s. These findings suggest that the framework offers strong potential for scalable, low-overhead security in resource-constrained IoT environments.

Keywords: Internet of Things (IoT); IoT security; artificial intelligence; blockchain; quantum-resistant cryptography; integrated security framework; performance modeling; edge computing; federated learning (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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