Theses Master's

FlexFHE: A System for Homomorphically Encrypting DNA and Operating on Encrypted Data Securely in Untrusted Environments

Attias, Lior

DNA data contains sensitive health information and personally identifiable data. Currently, even if DNA data is stored in encrypted databases, it must be decrypted for health professionals and researchers to analyze, which means that DNA data exists in plaintext on unsecured, untrusted servers and machines during analysis. This thesis describes a complete system for homomorphically encrypting DNA data in a trusted context and then running analytic operations on the encrypted DNA data in an untrusted context, thus allowing healthcare professionals and researchers to run both high volume analytics on many individuals’ sequenced DNA and run complex analytics on a single individual’s sequenced DNA without ever handling plaintext data.

Symmetric encryption is used as a mechanism for controlling which queries are made on the data. The threat model addressed by this system allows an authorized party to run only authorized queries on a genome, while restricting any additional access.

The system implemented achieves substring search, substring search with wildcards representing mutations, and percent match between two nucleotide sequences by converting genomic data into one-hot binary matrixes and encrypting each bit individually using OpenFHE’s LWE Encryption implemented using the CGGI scheme. While runtime for each operation is O(nm), each operation is maximally parallelized using OpenMP, thus allowing for accelerated performance on machines with multiple CPUs without the need for batching.


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More About This Work

Academic Units
Computer Science
Thesis Advisors
Bellovin, Steven Michael
M.S., Columbia University
Published Here
February 28, 2024


Code for the paper is located opensource at

Degree Program: Masters of Science in Computer Science, Columbia University Graduate School of Engineering and Applied Science
Academic Advisor: Steven Bellovin
Thesis or Dissertation: masters thesis
Degree Earned: Master of Science in Computer Science
Embargo Year(s): 0
Previously Published: false
Article Version:
Keywords: Fully Homomorphic Encryption, homomorphic substring search, OpenFHE, LWE Encryption, Genomic privacy, parallelized encrypted search on sequenced DNA, CGGI, homomorphic encryption, privacy preserving technology