ECG- PPS: Privacy Preserving Disease Diagnosis and Monitoring System for Real-Time ECG Signals

Beyazit B. Yuksel, Ayse Yilmazer-Metin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This study introduces the development of a state-of-the-art, real-time ECG monitoring and analysis system, incorporating cutting-edge medical technology and innovative data security measures. Our system performs three distinct functions: real-time ECG monitoring and disease detection, encrypted storage and synchronized visualization, and statistical analysis on encrypted data. At its core, the system uses a three-lead ECG preamplifier connected through a serial port to capture, display, and record real-time ECG data. These signals are securely stored in the cloud using robust encryption methods. Authorized medical personnel can access and decrypt this data on their computers, with AES encryption ensuring synchronized real-time data tracking and visualization. Furthermore, the system performs statistical operations on the ECG data stored in the cloud without decrypting it, using Fully Homomorphic Encryption (FHE). This enables privacy-preserving data analysis while ensuring the security and confidentiality of patient information. By integrating these independent functions, our system significantly enhances the security and efficiency of health monitoring. It supports critical tasks such as disease detection, patient monitoring, and preliminary intervention, all while upholding stringent data privacy standards. We provided detailed discussions on the system's architecture, hardware configuration, software implementation, and clinical performance. The results highlight the potential of this system to improve patient care through secure and efficient ECG monitoring and analysis. This work represents a significant leap forward in medical technology. By incorporating FHE into both data transmission and storage processes, we ensure continuous encryption of data throughout its lifecycle while enabling real-time disease diagnosis. Our entire architecture is available as open-source, encouraging further research and development in this vital field.

Original languageEnglish
Title of host publication2024 17th International Conference on Security of Information and Networks, SIN 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331509736
DOIs
Publication statusPublished - 2024
Event17th International Conference on Security of Information and Networks, SIN 2024 - Sydney, Australia
Duration: 2 Dec 20244 Dec 2024

Publication series

Name2024 17th International Conference on Security of Information and Networks, SIN 2024

Conference

Conference17th International Conference on Security of Information and Networks, SIN 2024
Country/TerritoryAustralia
CitySydney
Period2/12/244/12/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • disease-diagnosis
  • ecg
  • real-time
  • secure transmission

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