An Efficient Blockchain and Deep Learning-Based Framework for Secure Healthcare Data Management and Disease Prediction

Healthcare data security is a pressing concern given the surge in data breaches, with over 750 incidents reported in 2021 alone, exposing more than 193 million personal records. This paper introduces an Efficient Data Security System that leverages smart contracts, WEB 3.0 deep learning algorithms, and blockchain technology to address these challenges. The system provides robust data protection by eliminating the need for encryption keys, utilizing blockchain for tamper-proof storage, and incorporating advanced deep learning algorithms for predictive analytics. The framework of WEB 3.0 integrates blockchain at the backend, ensuring secure and immutable data storage. Smart contracts enable automated and transparent data access without compromising security. Additionally, the system utilizes the InterPlanetary File System (IPFS) for efficient image storage and retrieval, enhancing data accessibility while maintaining cryptographic security. The integration of deep learning algorithms enables predictive analytics for medical conditions such as Alzheimer's disease and tumor detection, further enhancing the system's capabilities in healthcare data management and analysis.