Designing an Attribute-Based Encryption Scheme with an Enhanced Anonymity Model for Privacy Protection in E-Health

作     者：Zala, Kirtirajsinh Thakkar, Hiren Kumar Dholakia, Neel Shukla, Madhu Thumar, Deep 

作者机构：Department of Information Technology Marwadi University Gujarat Rajkot 360006 India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gujarat Gandhinagar 382007 India Department of Computer Engineering Marwadi University Gujarat Rajkot 360006 India Faculty of Engineering Marwadi Education Foundations Gujarat Rajkot 360006 India 

出 版 物：《SN Computer Science》 (SN COMPUT. SCI.)

年 卷 期：2024年第5卷第2期

页      面：203页

主　　题：Anonymity Attribute-based encryption (ABE) Cloud computing E-health Privacy Secure hash algorithm (SHA-1) 

摘      要：The medical field and the health care industry generate large volumes of data that are ultimately beneficial to society. Yet, the exposure of sensitive aspects might jeopardize this data generation. Exposure to Healthcare Information made available via the internet with the intention of benefiting healthcare professionals presents a challenge for researchers in terms of privacy and security concerns. This access is intended to benefit the medical community. With growing technology, medical data on the cloud are subject to unanticipated dangers, and the threat landscape appears resilient with sensitive qualities. Organizations fail to keep their reputations and are unable to maintain public trust in our modern day. The severity of advanced security threats compromises patient data privacy and healthcare unit security. Many studies and practitioners’ fruitful approaches gave up healing resolutions, but the requirement for a perfect solution remains unsatisfactory. In this research, we provide a solution for dealing with security challenges in healthcare administration. We present a hybrid system that combines sensitive attribute access primitives with enhanced attribute-based encryption and anonymity methods. The proposed approach electronic health records design model is closely linked with the proposed approach and system scenario, forming a comprehensive blueprint for our healthcare technology solution. In terms of completion time when user instance is upto 500, the practical flexible ABE instances method outperforms the other approaches such as real-time operational data base extraction–transformation–loading, and long short-term memory to recurrent neural network by a significant margin. This method offers the quick encryption (7.5 s), decryption (5.4 s), and reduced memory usage (5361 s). A cloud sim simulator is used to evaluate the proposed mechanism’s performance, encryption, decryption, and memory usage. The latest model with better hardware and software opt