Combining hashing and enciphering algorithms for epidemiological analysis of gathered data

Area of Science:

• Health Informatics
• Data Security
• Public Health Research

Background:

• Multi-center studies require compiling individual records from diverse sources.
• Anonymization procedures are crucial for legal compliance in data handling.
• Current anonymization methods with study-specific keys hinder record linkage across collections.

Purpose of the Study:

• To develop a secure and linkable data anonymization methodology for multi-center studies.
• To address the challenge of connecting disparate datasets while adhering to legal security requirements.
• To facilitate the use of health data in public health research without compromising patient privacy.

Main Methods:

• A novel approach combining hashing and asymmetric encryption techniques.
• Utilizes two keys, with the private key uniquely dependent on the patient's identity.
• Ensures data integrity and confidentiality through cryptographic methods.

Main Results:

• The integrated hashing and enciphering techniques significantly enhance data security.
• The proposed scheme offers a robust solution for protecting sensitive health information.
• Improved security is achieved without impeding the ability to link records.

Conclusions:

• The developed methodology enables secure data utilization for public health.
• It effectively balances the need for data accessibility with stringent legal security requirements.
• This approach supports collaborative research by allowing secure data linkage across institutions.