Abstract
The rapid progress in genome sequencing technologies leads to availability of high amounts of genomic data. Accelerating the pace of biomedical breakthroughs and discoveries necessitates not only collecting millions of genetic samples but also granting open access to genetic databases. However, one growing concern is the ability to protect the privacy of sensitive information and its owner. In this work, we survey a wide spectrum of cross-layer privacy breaching strategies to human genomic data (using both public genomic databases and other public non-genomic data). We outline the principles and outcomes of each technique, and assess its technological complexity and maturation. We then review potential privacy-preserving countermeasure mechanisms for each threat.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
SNPs are the main cause for variations in the human genome. They are also responsible for the differences in our phenotypes/traits and genotypes.
- 2.
The allele frequency represents the incidence of a gene variant at a given gene location in a population gene pool.
References
Ayday, E., Raisaro, J.L., Hengartner, U., et al.: Privacy-preserving processing of raw genomic data. In: Proceedings of 8th Data Privacy Management (DPM 2013) International Workshop (in conjunction with ESORICS) (2013)
Ayday, E., Raisaro, J.L., et al.: Protecting and evaluating genomic privacy in medical tests and personalized medicine. In: Proceedings of the 12th ACM Workshop on Privacy in the Electronic Society, pp. 95–106. ACM (2013)
Baldi, P., Baronio, R., et al.: Countering GATTACA: efficient and secure testing of fully-sequenced human genomes. In: Proceedings of the 18th ACM Conference on Computer and Communications Security, pp. 691–702. ACM (2011)
Erlich, Y., Narayanan, A.: Routes for breaching and protecting genetic privacy. Nat. Rev. Genet. 15(6), 409–421 (2014)
Galperin, M.Y., et al.: The 2015 nucleic acids research database issue and molecular biology database collection. Nucleic Acids Res. 43(D1), D1–D5 (2015)
Gymrek, M., McGuire, A.L., Golan, D., Halperin, E., Erlich, Y.: Identifying personal genomes by surname inference. Science 339(6117), 321–324 (2013)
Homer, N., Szelinger, S., Redman, M., Duggan, D., Tembe, W., et al.: Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 4(8), e1000167 (2008)
Humbert, M., Ayday, E., et al.: Addressing the concerns of the lacks family: quantification of kin genomic privacy. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, pp. 1141–1152. ACM (2013)
Iossifov, I., ORoak, B.J., Sanders, S.J., et al.: The contribution of de novo coding mutations to autism spectrum disorder. Nature 515(7526), 216–221 (2014)
Kayser, M., de Knijff, P.: Improving human forensics through advances in genetics, genomics and molecular biology. Nat. Rev. Genet. 12(3), 179–192 (2011)
Kobayashi, E., Sakurada, T., et al.: Public involvement in pharmacogenomics research: a national survey on patients attitudes towards pharmacogenomics research and the willingness to donate DNA samples to a DNA bank in japan. Cell Tissue Banking 12(2), 71–80 (2011)
Naveed, M., Ayday, E., Clayton, E.W., Fellay, J., Gunter, C.A., Hubaux, J.P., Malin, B.A., Wang, X.: Privacy in the genomic era. ACM Comput. Surv. (CSUR) 48(1), 6 (2015)
Nyholt, D.R., Yu, C.E., Visscher, P.M.: On jim watson’s APOE status: genetic information is hard to hide. Eur. J. Hum. Genet. 17(2), 147 (2009)
Pakstis, A.J., Speed, W.C., Fang, R., Hyland, F.C., et al.: SNPs for a universal individual identification panel. Hum. Genet. 127(3), 315–324 (2010)
Schadt, E.E., Woo, S., Hao, K.: Bayesian method to predict individual SNP genotypes from gene expression data. Nat. Genet. 44(5), 603–608 (2012)
Storr, C.L., Or, F., et al.: Genetic research participation in a young adult community sample. J. Commun. Genet. 5(4), 363–375 (2014)
Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(05), 557–570 (2002)
Sweeney, L., Abu, A., Winn, J.: Identifying participants in the personal genome project by name. Available at SSRN 2257732 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Alser, M., Almadhoun, N., Nouri, A., Alkan, C., Ayday, E. (2016). Can you Really Anonymize the Donors of Genomic Data in Today’s Digital World?. In: Garcia-Alfaro, J., Navarro-Arribas, G., Aldini, A., Martinelli, F., Suri, N. (eds) Data Privacy Management, and Security Assurance. DPM QASA 2015 2015. Lecture Notes in Computer Science(), vol 9481. Springer, Cham. https://doi.org/10.1007/978-3-319-29883-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-29883-2_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-29882-5
Online ISBN: 978-3-319-29883-2
eBook Packages: Computer ScienceComputer Science (R0)