Private queries on encrypted genomic data.

Area of Science:

• Cryptography
• Bioinformatics
• Secure Computation

Background:

• The iDASH Secure Genome Analysis Competition (2016) focused on privacy-preserving queries for homomorphically encrypted genomic data.
• The challenge involved encrypting large mutation datasets for secure cloud storage and querying without data or query disclosure.

Purpose of the Study:

• To develop a novel string matching protocol for privacy-preserving queries on homomorphically encrypted data.
• To enable efficient and secure querying of genomic datasets stored in the cloud.

Main Methods:

• Combined homomorphic encryption techniques with private set intersection protocols.
• Developed a novel string matching protocol to minimize computational and communication costs.
• Implemented the protocol using the SEAL v2.1 homomorphic encryption library.

Main Results:

• Achieved an efficient solution for the iDASH competition task.
• Demonstrated a running time of 4 seconds and a communication cost of 2 MB for querying 5 mutations in a 100,000-mutation dataset using 8 threads.
• Validated the feasibility of privacy-preserving queries on realistic-sized encrypted genomic datasets.

Conclusions:

• Homomorphic encryption enables efficient privacy-preserving mutation querying in large genomic datasets.
• The developed protocol is applicable to various data types beyond genomics.
• The protocol holds independent interest for the homomorphic encryption research community.