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Efficient privacy-preserving string search and an application in genomics.

Kana Shimizu1, Koji Nuida2, Gunnar Rätsch3

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This study introduces a privacy-preserving method for searching personal genomes. The new algorithm efficiently protects user queries and genomic data, offering a significant speed improvement over existing methods.

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Area of Science:

  • Bioinformatics
  • Genomic Data Privacy
  • Computational Biology

Background:

  • Personal genomes present significant privacy risks.
  • Protecting genomic data during searches is a major challenge.
  • Current methods lack efficient privacy-preserving search capabilities.

Purpose of the Study:

  • To develop a novel, privacy-preserving algorithm for searching genetic information within large genomic databases.
  • To ensure both user query confidentiality and server database integrity.
  • To enhance the security of personal genome data access.

Main Methods:

  • Combined the Burrows-Wheeler transform (BWT) with additive homomorphic encryption.
  • Utilized oblivious transfer to conceal sequence queries and genomic regions.
  • Developed an efficient algorithm for searching single nucleotide polymorphism (SNP) sequences.

Main Results:

  • The algorithm enables users to identify the longest sequence match without revealing their query to the server.
  • Experimental results on 2184 genomes from the 1000 Genomes Project showed query times of 4.6s (client) and 10.8s (server).
  • The implemented algorithm is over ten times faster than a baseline exhaustive search approach.

Conclusions:

  • The proposed method offers an efficient and secure solution for private genomic data searching.
  • This approach significantly advances the field of genomic privacy and data security.
  • The algorithm is publicly available for further research and application.