An AI-Driven Framework for Integrated Security and Privacy in Internet of Things Using Quantum-Resistant Blockchain DOI Creative Commons
Mahmoud Elkhodr

Future Internet, Год журнала: 2025, Номер 17(6), С. 246 - 246

Опубликована: Май 30, 2025

The growing deployment of the Internet 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 Integrated Adaptive Security Framework for IoT (IASF-IoT), which integrates artificial intelligence, blockchain technology, quantum-resistant cryptography into a unified solution tailored environments. Central framework is an adaptive AI-driven orchestration mechanism, complemented by blockchain-based identity management, lightweight protocols, Digital Twins predict proactively mitigate threats. A theoretical performance model large-scale simulation involving 1000 heterogeneous devices were used evaluate framework. Results showed IASF-IoT achieved detection accuracy between 85% 99%, with simulated energy consumption remaining below 1.5 mAh per day response times averaging around 2 s. These findings suggest offers strong potential scalable, low-overhead in resource-constrained

Язык: Английский

An AI-Driven Framework for Integrated Security and Privacy in Internet of Things Using Quantum-Resistant Blockchain DOI Creative Commons
Mahmoud Elkhodr

Future Internet, Год журнала: 2025, Номер 17(6), С. 246 - 246

Опубликована: Май 30, 2025

The growing deployment of the Internet 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 Integrated Adaptive Security Framework for IoT (IASF-IoT), which integrates artificial intelligence, blockchain technology, quantum-resistant cryptography into a unified solution tailored environments. Central framework is an adaptive AI-driven orchestration mechanism, complemented by blockchain-based identity management, lightweight protocols, Digital Twins predict proactively mitigate threats. A theoretical performance model large-scale simulation involving 1000 heterogeneous devices were used evaluate framework. Results showed IASF-IoT achieved detection accuracy between 85% 99%, with simulated energy consumption remaining below 1.5 mAh per day response times averaging around 2 s. These findings suggest offers strong potential scalable, low-overhead in resource-constrained

Язык: Английский

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