Fortified IoT-Fog framework for enhanced healthcare intelligence

Healthcare systems face challenges in certifying the security, accuracy, and efficiency of data gathered from IoT sensors. Confidentiality and integrity of patient information are paramount while optimizing resource usage remains a concern. This study introduces a novel approach called Radial-based Elliptical Curve Blockchain (RbECB) to address the monitoring and security aspects of IoT-sensed data. The method integrates cryptographic techniques to enhance data confidentiality. Data pre-processing was conducted followed by the implementation of RbECB for secure data management. IFogSim was utilized to optimize fog computing efficiency and reduce communication costs between fog nodes with IoT devices. The proposed RbECB method significantly improved data security, accuracy, and efficiency in healthcare applications. Evaluation results demonstrated enhanced performance in terms of accuracy at 99%, reduced encryption time of 75 ms, improved confidentiality of 99%, optimized energy consumption of 107,785.34 kJ, bandwidth utilization for node 1 of 0.9 GB/s, for node 2 for 2 GB/s, for node 3 having 4 GB/s, for node 4 having 4.5 GB/sand for node 5 having 4.8 GB/s, and reduced error rates with 0.15% and overall efficiency of 98%. This study underscores the potential of RbECB and Fog computing in advancing intelligent healthcare systems, ensuring safer and more efficient data management while complying with stringent privacy regulations.