BEDCrypt: Privacy-preserving interval analytics with homomorphic encryption

TL;DR

BEDCrypt is a system that uses homomorphic encryption to enable privacy-preserving genomic interval analysis, allowing secure computation on sensitive genomic data without revealing plaintext information to the server.

Contribution

It introduces BEDCrypt, a novel homomorphic encryption-based framework for secure genomic interval analytics in an honest-but-curious server setting.

Findings

Supports core genomic analyses like coverage summaries and interval intersections.

Ensures data and query privacy by operating on encrypted data.

Enables secure set-similarity statistics without exposing plaintext information.

Abstract

Motivation. Genomic data and derived interval datasets can carry sensitive information, and the analysis itself can reveal an analyst's intent. As genomic workloads are increasingly outsourced to third-party infrastructure, there is a need for privacy-preserving technologies that protect both the data and the queried loci. Results. We present BEDCrypt, a privacy-preserving system for genomic interval analytics based on homomorphic encryption in an honest-but-curious server setting. The server operates only on encrypted data and returns encrypted answers that the client decrypts locally, enabling core functionalities such as coverage summaries, interval intersections, proximity (window-style) queries, and set-similarity statistics, without revealing plaintext intervals or query genomic locations to the server.