BEDCrypt: Privacy-preserving interval analytics with homomorphic encryption

Fuente: arXiv
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Main Authors: Provatas, Kimon Antonios, Georgakopoulos-Soares, Ilias
Format: Preprint
Published: 2026
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author Provatas, Kimon Antonios
Georgakopoulos-Soares, Ilias
author_facet Provatas, Kimon Antonios
Georgakopoulos-Soares, Ilias
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2602_21994
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle BEDCrypt: Privacy-preserving interval analytics with homomorphic encryption
Provatas, Kimon Antonios
Georgakopoulos-Soares, Ilias
Genomics
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.
title BEDCrypt: Privacy-preserving interval analytics with homomorphic encryption
topic Genomics
url https://arxiv.org/abs/2602.21994