Multi-Level Data-Security and Data-Protection in a Distributed Search Infrastructure for Digital Medical Samples.

Area of Science:

• Bioinformatics and Health Informatics
• Data Management and Security

Background:

• Human sample data is stored in biobanks, managed by specialized software for digital derived data.
• Integrating these stand-alone systems with a search infrastructure allows researchers to access data from diverse sources.

Purpose of the Study:

• To investigate concepts for a multi-level security architecture for connected biobank data systems.
• To address key challenges including data protection, patient rights, data heterogeneity, and access control.

Main Methods:

• Conceptual investigation of security architectures.
• Analysis of requirements for integrated biobank data systems.

Main Results:

• Identified critical challenges in data protection, patient rights, data heterogeneity, and access control.
• Proposed a conceptual multi-level security architecture framework.

Conclusions:

• A multi-level security architecture is essential for compliant and effective integration of biobank data.
• Addressing these challenges is crucial for enabling secure and ethical research data sharing.