Encryption method for secure storage and analysis of patient data on the cloud

This technology is a secure protocol that preserves patient data privacy during cloud-based storage and computation, while reducing storage demand.

Unmet Need: Privacy-preserving analysis of sensitive patient data

Precision medicine generates massive genomic and phenotypic datasets. Yet, the sensitive nature and lack of uniform privacy regulations across different jurisdictions create major barriers to secure cloud storage, analysis, and collaboration. Conventional approaches often require downloading and decrypting the data to perform analysis, which increases privacy risks and limits scalability. Therefore, a method that allows confidential multi-user analysis of encrypted patient data is critically needed.

The Technology: Homomorphic encryption enabling secure multi-user genomic analysis

This technology utilizes homomorphic encryption, combined with public-key switching, to enable multiple users to query and analyze genotype-phenotype datasets while the data remain encrypted in the cloud. The protocol supports common analyses while protecting the underlying patient information. Ciphertext storage packing further minimizes cloud storage requirements and improves computational efficiency. This secure, scalable framework enables collaborative research and clinical data analysis without compromising patient confidentiality.

Applications:

  • Data management system for genotype-phenotype data
  • Encrypted database system
  • Privacy-preserving storage and analysis systems for large-scale patient data

Advantages:

  • Privacy protection
  • Minimizes storage space
  • Enables multi-user analysis of datasets while preserving patients’ confidentiality

Lead Inventor:

Gamze Gursoy, Ph.D.

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