A Novel Homomorphic Encryption and Consortium Blockchain-based Hybrid Deep Learning Model for Industrial Internet of Medical Things

• Published in: IEEE transactions on network science and engineering Vol. 10; no. 5; pp. 1 - 18
• Main Authors: Ali, Aitizaz, Pasha, Muhammad Fermi, Guerrieri, Antonio, Guzzo, Antonella, Sun, Xiaobing, Saeed, Aamir, Hussain, Amir, Fortino, Giancarlo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Blockchain; Blockchains; Cloud computing; Consortia; Cryptography; Cybersecurity; Data models; Data privacy; Deep learning; Denial of service attacks; Distributed ledger; Electronic health records; Electronic Medical Records; Encryption; Health care; Homomorphic encryption; Hybrid Deep Learning; Industrial Internet of Medical Things; Internet; Internet of medical things; Machine Learning; Medical services; Performance measurement; Privacy; Security; Smart contracts

Securing Electronic Medical Records (EMRs) is one of the most critical applications of cryptography over the Internet due to the value and importance of data contained in such EMRs. Although blockchain-based healthcare systems can provide security, privacy, and immutability to EMRs, several outstand...