AN IOT-ASSISTED LIGHTWEIGHT PROACTIVE PROVABLE BLOCKCHAIN SECURITY FRAMEWORK FOR SECURE HEALTHCARE DATA TRANSMISSION IN DECENTRALIZED CLOUD ENVIRONMENTS

Abstract

             In the past few years, Health-IoT has expanded significantly as demand for IoT-based health-tech devices has skyrocketed. Although healthcare IoT devices produce a staggering quantity of private patient information, there are significant challenges associated with securely, quickly and accurately transmitting that information. Several common transmission protocols typically overuse storage and processing resources and do not offer fast or reliable real-time verification and/or tracking options. These limitations lead to various security risks including the ability for hackers to illegally gain access to patient information, change data without detection, and disclose private patient confidentiality. In an effort to help mitigate these challenges, we introduce an IoT-Assisted Lightweight Proactive Provable Blockchain Security (LP2 - BCS) framework that enables secure health-care information transmission through the use of decentralized cloud computing. Our LP2 -BCS framework combines four core algorithms that work together to provide comprehensive data security and transmission performance. The Secure Log Hash Indexing (SL-HBI) algorithm provides a method for authenticating transactions and creating unique hash-indexed blocks, ensuring integrity and Traceability of all transactions. The Adaptive Lightweight Flip-Shuffle Folding Encryption Algorithm (AL-FSFEA) uses lightweight but strongly encrypted protocols, suitable for use on resource-constrained IoT devices, thus allowing us to efficiently encrypt sensitive health care information while minimizing operational costs (both in terms of electricity and equipment). The Provable Blockchain, Lightweight Encryption (PBL-IM) algorithm enables us to build a secure, tamper-resistant network of interconnected IoT devices while providing robust monitoring capabilities for detecting and verifying transaction anomalies, thereby assuring patient confidentiality and integrity. Finally, the Master Node Authentication and Aggregation (MNAA), algorithm authenticates all participant nodes and creates a single trusted group of nodes that can be used as representatives within the overall transaction environment for the successful completion of secure health care information transfers. The effectiveness of the framework is assessed through the use of eight performance metrics to measure the performance of the framework, including: encryption and decryption time, transaction latency, throughput, energy consumption, data integrity, key management efficiency, and attack detection accuracy.