| Full text | |
| Author(s): |
Mosaiyebzadeh, Fatemeh
;
Pouriyeh, Seyedamin
;
Parizi, Reza M.
;
Sheng, Quan Z.
;
Han, Meng
;
Zhao, Liang
;
Sannino, Giovanna
;
Ranieri, Caetano Mazzoni
;
Ueyama, Jo
;
Batista, Daniel Macedo
Total Authors: 10
|
| Document type: | Journal article |
| Source: | ELECTRONICS; v. 12, n. 12, p. 28-pg., 2023-06-01. |
| Abstract | |
Advancements in wearable medical devices using the IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), efficient healthcare services can be provided to patients. Healthcare professionals have effectively used AI-based models to analyze the data collected from IoHT devices to treat various diseases. Data must be processed and analyzed while avoiding privacy breaches, in compliance with legal rules and regulations, such as the HIPAA and GDPR. Federated learning (FL) is a machine learning-based approach allowing multiple entities to train an ML model collaboratively without sharing their data. It is particularly beneficial in healthcare, where data privacy and security are substantial concerns. Even though FL addresses some privacy concerns, there is still no formal proof of privacy guarantees for IoHT data. Privacy-enhancing technologies (PETs) are tools and techniques designed to enhance the privacy and security of online communications and data sharing. PETs provide a range of features that help protect users' personal information and sensitive data from unauthorized access and tracking. This paper comprehensively reviews PETs concerning FL in the IoHT scenario and identifies several key challenges for future research. (AU) | |
| FAPESP's process: | 21/10921-2 - Image processing for flood detection and prediction |
| Grantee: | Caetano Mazzoni Ranieri |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 14/50937-1 - INCT 2014: on the Internet of the Future |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 15/24485-9 - Future internet for smart cities |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |