An IoT-Based Anonymous Function for Security and Privacy in Healthcare Sensor Networks

Area of Science:

• Computer Science
• Healthcare Technology
• Cybersecurity

Background:

• The integration of the Internet of Things (IoT) in healthcare offers significant potential for improving healthcare delivery.
• However, connected medical devices introduce substantial security risks, including data breaches and patient privacy violations.
• Securing sensitive health information in IoT environments is paramount due to the ubiquitous nature of these devices.

Purpose of the Study:

• To present a novel algorithm for anonymizing sensitive health data exchanged within IoT-based healthcare communication systems.
• To enhance the security and privacy of patient data transmitted wirelessly.
• To ensure the confidentiality of user interactions during online data sessions.

Main Methods:

• Development of a data anonymization algorithm specifically for IoT healthcare environments.
• Implementation of a secure encryption process to enable health data anonymity.
• Validation of the algorithm's effectiveness using mathematical function analysis.

Main Results:

• The proposed algorithm effectively anonymizes sensitive health data, protecting user privacy.
• Mathematical analysis confirmed the algorithm's strong anonymity functions.
• The developed solution guarantees safety features for IoT systems in healthcare communication.

Conclusions:

• The presented anonymization algorithm provides a robust solution for securing sensitive health data in IoT environments.
• This research contributes to enhancing patient privacy and data security in the evolving landscape of digital healthcare.
• The algorithm ensures the integrity and confidentiality of health information, mitigating risks associated with connected medical devices.