The Integrated Holistic Security and Privacy Framework Deployed in CrowdHEALTH Project.

Area of Science:

• Health Informatics
• Cybersecurity
• Data Privacy

Background:

• Ensuring the security and confidentiality of electronic health records (EHRs) is crucial for both individuals and healthcare providers.
• Trust in EHR systems hinges on robust protection of personal health information.

Purpose of the Study:

• To develop a comprehensive security and privacy framework for the CrowdHEALTH project.
• The framework aims to guarantee data confidentiality, integrity, and availability in compliance with GDPR.

Main Methods:

• Implementation of Privacy Enhancing Technologies (PETs) to adhere to GDPR data protection regulations.
• Deployment of OpenID Connect for flexible, scalable, and lightweight user authentication.
• Integration of an Attribute-Based Access Control (ABAC) mechanism for efficient policy creation.

Main Results:

• CrowdHEALTH integrates ABAC with OpenID Connect, establishing a scalable foundation for user authorization.
• The security framework seamlessly interacts with other components, including the Big Data Platform, ensuring authenticated data access.
• Identified requirements for a Trust and Reputation Model to manage interactions with low-trust data sources.

Conclusions:

• The CrowdHEALTH Integrated Holistic Security and Privacy framework meets e-health security criteria through mechanisms like authentication, authorization, access control, anonymization, and reputation modeling.
• Further testing is required to validate the framework's robustness and performance.
• The framework is adaptable to evolving legislative requirements for cross-border e-health systems.