Towards Secure IoT Authentication System Based on Fog Computing and Blockchain Technologies to Resist 51% and Hijacking Cyber-Attacks

The Internet of Health Things (IoHT) is a network of healthcare devices, software, and systems that enable remote monitoring and healthcare services by gathering real-time health data through sensors. Despite its significant benefits for modern smart healthcare, IoHT faces growing security challenges due to the limited processing power, storage capacity, and self-defense capabilities of its devices. While blockchain-based authentication solutions have been developed to leverage tamper-resistant decentralized designs for enhanced security, they often require substantial computational resources, increased storage, and longer authentication times, hindering scalability and time efficiency in large-scale, time-critical IoHT systems. To address these challenges, we propose a novel four-phase authentication scheme comprising setup, registration, authentication, and secret construction phases. Our scheme integrates chaotic-based public key cryptosystems, a Light Encryption Device (LED) with a 3-D Lorenz chaotic map algorithm, and blockchain-based fog computing technologies to enhance both efficiency and scalability. Simulated on the Ethereum platform using Solidity and evaluated with the JMeter tool, the proposed scheme demonstrates superior performance, with a computational cost reduction of 40% compared to traditional methods like Elliptic Curve Cryptography (ECC). The average latency for registration is 1.25 ms, while the authentication phase completes in just 1.50 ms, making it highly suitable for time-critical IoHT applications. Security analysis using the Scyther tool confirms that the scheme is resistant to modern cyberattacks, including 51% attacks and hijacking, while ensuring data integrity and confidentiality. Additionally, the scheme minimizes communication costs and supports the scalability of large-scale IoHT systems. These results highlight the proposed scheme's potential to revolutionize secure and efficient healthcare monitoring, enabling real-time, tamper-proof data management in IoHT environments. [JJCIT 2025; 11(2.000): 238-259]