research-article

Privacy-preserving genomic computation through program specialization

Authors:

Michael K. Reiter,

Zheng DongAuthors Info & Claims

CCS '09: Proceedings of the 16th ACM conference on Computer and communications security

Pages 338 - 347

https://doi.org/10.1145/1653662.1653703

Published: 09 November 2009 Publication History

Abstract

In this paper, we present a new approach to performing important classes of genomic computations (e.g., search for homologous genes) that makes a significant step towards privacy protection in this domain. Our approach leverages a key property of the human genome, namely that the vast majority of it is shared across humans (and hence public), and consequently relatively little of it is sensitive. Based on this observation, we propose a privacy-protection framework that partitions a genomic computation, distributing the part on sensitive data to the data provider and the part on the pubic data to the user of the data. Such a partition is achieved through program specialization that enables a biocomputing program to perform a concrete execution on public data and a symbolic execution on sensitive data. As a result, the program is simplified into an efficient query program that takes only sensitive genetic data as inputs. We prove the effectiveness of our techniques on a set of dynamic programming algorithms common in genomic computing. We develop a program transformation tool that automatically instruments a legacy program for specialization operations. We also demonstrate that our techniques can greatly facilitate secure multi-party computations on large biocomputing problems.

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Index Terms

Privacy-preserving genomic computation through program specialization
1. Security and privacy
  1. Cryptography
    1. Cryptanalysis and other attacks
  2. Intrusion/anomaly detection and malware mitigation
2. Social and professional topics
  1. Computing / technology policy
    1. Computer crime

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cover image ACM Conferences

CCS '09: Proceedings of the 16th ACM conference on Computer and communications security

November 2009

664 pages

ISBN:9781605588940

DOI:10.1145/1653662

General Chair:
Ehab Al-Shaer
University of North Carolina, Charlotte, USA
,
Program Chairs:
Somesh Jha
University of Wisconsin, USA
,
Angelos D. Keromytis
Columbia University, USA and Symantec Research Labs Europe, France

Copyright © 2009 ACM.

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https://doi.org/10.1109/ICEIEC61773.2024.10561732
Zhu DZhu HWang XLu RFeng D(2023)Efficient and Privacy-Preserving Similar Patients Query Scheme Over Outsourced Genomic DataIEEE Transactions on Cloud Computing10.1109/TCC.2021.313128711:2(1286-1302)Online publication date: 1-Apr-2023
https://doi.org/10.1109/TCC.2021.3131287
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https://doi.org/10.1007/978-3-031-24337-0_23
Vu XJiang L(2023)Self-adaptive Privacy Concern Detection for User-Generated ContentComputational Linguistics and Intelligent Text Processing10.1007/978-3-031-23793-5_14(153-167)Online publication date: 26-Feb-2023
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