Personal genome privacy protection with feature-based hierarchical dual-stage encryption

Xukai Zou, Peng Liu, Jake Y. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Personal Genomic information is becoming increasingly important to both scientific research and clinical practice. However, security breach, misuse, or unintended disclosure of this information may result in severe privacy breaches. Traditional privacy preservation of personal genome information is implemented in an "all-or-none" manner, i.e., an entire genome being controlled as either fully accessible or fully inaccessible. In this paper, we propose a new fine-grained privacy protection method for flexible multi-level genome information protection and access. The method can make use of any user-defined hierarchical knowledge structure to define privacy levels and control cryptography-based hierarchical access. It also implements dual-stage encryptions to allow efficient definition, addition, and update of feature-based privacy protections. The experiments show that it can be effectively implemented to deal with real personal genome data sets in the future.

Original languageEnglish (US)
Title of host publicationProceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
PublisherIEEE Computer Society
Pages178-181
Number of pages4
ISBN (Print)9781467304900
DOIs
StatePublished - Jan 1 2011
Event2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11 - San Antonio, TX, United States
Duration: Dec 4 2011Dec 6 2011

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
CountryUnited States
CitySan Antonio, TX
Period12/4/1112/6/11

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

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