Generative Federated Learning With Small and Large Models in Consumer Electronics for Privacy-Preserving Data Fusion in Healthcare Internet of Things
Al-Ahliyya Amman University · National University of Malaysia · +6 more institutions
Abstract
Healthcare Internet of Things (HIoT) requires large-scale privacy features to ensure maximum security in sharing sensitive physiological data in consumer electronics. Recent approaches utilize the fusion concept to provide maximum privacy in health data sharing. Embedded signing data fusion with the health observed data ensures privacy preserved sharing across heterogeneous medical consumer devices for diagnosis. This article proposes a Dependency-correlated Data Fusion Scheme (DcDFS) to maximize the privacy of the health data-sharing process. The proposed scheme prepares separate key signing procedures using triple-DES (data encryption standard) to embed with the accumulated health data. The fusion process is…
Citation impact
- FWCI
- 122.39
- Percentile
- 100%
- References
- 53
Authors
10Topics & keywords
- Internet of Things
- The Internet
- Computer science
- Sensor fusion
- Electronics
- Information privacy
- Health care
- Generative grammar