Cloud-IIoT-Based Electronic Health Record Privacy-Preserving by CNN and Blockchain-Enabled Federated Learning

【Author】 Alzubi, Jafar A.; Alzubi, Omar A.; Singh, Ashish; Ramachandran, Manikandan

【Source】IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

【影响因子】11.648

【Abstract】Industrial cloud computing and Internet of Things have transformed the healthcare industry with the rapid growth of distributed healthcare data. Security and privacy of healthcare data are crucial challenges in the healthcare industry. This article proposes a novel technique using deep learning and blockchain techniques for electronic health record privacy-preservation. The processed dataset classified normal and abnormal users using the convolutional neural network approach. Then, by using blockchain integrated with a cryptography-based federated learning module, the abnormal users have been processed and removed from the database along with the accessibility for the health records. The simulation has been done in the Python tool and experimental results show that the model's classification results and performance are better than other existing techniques.

【Keywords】Medical services; Security; Data privacy; Data models; Blockchains; Convolutional neural networks; Collaborative work; Blockchain-enabled federated learning; cloud-Industrial Internet of Things (IIoT); convolutional neural network (CNN); healthcare industry; privacy preservation

【发表时间】2023 JAN

【收录时间】2022-11-30

【文献类型】实证数据

【主题类别】

区块链技术-协同技术-物联网