Private Epigenetic PaceMaker Detector Using Homomorphic Encryption - Extended Abstract

Meir Goldenberg, Sagi Snir, Adi Akavia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The Epigenetic Pacemaker (EPM) model uses DNA methylation data to predict human epigenetic age. The methylation values are collected from different individuals and are considered to be of medical importance. Sharing this data publicly among labs and other third parties for model calculation purposes may violate the privacy of personal medical records. The use of standard encryption approaches can prevent the exposure of these personal records to third parties, when at rest, but running computations on the data requires decrypting it first, and thus exposing the data to the computing party. This work proposes computing EPM while limiting data exposure by employing cryptographic secure computing techniques including homomorphic encryption. Our protocol has rigorous privacy guarantees against computationally bounded adversaries in the two-server model. We implemented a relaxed version of the protocol showing good correlation with low accuracy error between the model computed with and without encryption.

Original languageEnglish
Title of host publicationBioinformatics Research and Applications - 18th International Symposium, ISBRA 2022, Proceedings
EditorsMukul S. Bansal, Zhipeng Cai, Serghei Mangul
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783031231971
StatePublished - 2022
Event18th International Symposium on Bioinformatics Research and Applications, ISBRA 2022 - Haifa, Israel
Duration: 14 Nov 202217 Nov 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13760 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Symposium on Bioinformatics Research and Applications, ISBRA 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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