Abstract
Geneticists prefer to store patients’ aligned, raw genomic data, in addition to their variant calls (compact and summarized form of the raw data), mainly because of the immaturity of bioinformatic algorithms and sequencing platforms. Thus, we propose a privacy-preserving system to protect the privacy of aligned, raw genomic data. The raw genomic data of a patient includes millions of short reads, each comprised of between 100 and 400 nucleotides (genomic letters). We propose storing these short reads at a biobank in encrypted form. The proposed scheme enables a medical unit (e.g., a pharmaceutical company or a hospital) to privately retrieve a subset of the short reads of the patients (which include a definite range of nucleotides depending on the type of the genetic test) without revealing the nature of the genetic test to the biobank. Furthermore, the proposed scheme lets the biobank mask particular parts of the retrieved short reads if (i) some parts of the provided short reads are out of the requested range, or (ii) the patient does not give consent to some parts of the provided short reads (e.g., parts revealing sensitive diseases). We evaluate the proposed scheme to show the amount of unauthorized genomic data leakage it prevents. Finally, we implement the proposed scheme and assess its practicality.
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- 1.
Alignment is with respect to the reference genome, which is assembled by the scientists.
- 2.
Knowing the MU (e.g., the name of the hospital) the biobank could de-anonymize an individual using other sources (e.g., by associating the time of the test and the location of the MU with the location patterns of the victim).
- 3.
Following our discussions with geneticists and medical doctors, we conclude that the patient’s involvement in the genetic tests is not desired for the practicality of the protocol (e.g., when a pharmaceutical company conducts genetic research on thousands of patients).
- 4.
We reveal the real identity of the MU to the biobank to make sure that the request comes from a valid source.
- 5.
\(\mathrm {\Omega }_P\) denotes the positions on the patient’s genome for which the patient does not give consent to the original request owner (e.g., specialized sub-unit at the MU).
- 6.
We assume that the biobank has a list of valid MUs, whose requests it will answer.
- 7.
The generation of the decryption keys for the SC is the same as the generation of the encryption keys as we discussed in Sect. 5.1.
References
Agrawal, R., Kiernan, J., Srikant, R., Xu, Y.: Order preserving encryption for numeric data. In: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data, pp. 563–574 (2004)
Ayday, E., Cristofaro, E.D., Tsudik, G., Hubaux, J.P.: The chills and thrills of whole genome sequencing. arXiv:1306.1264 (2013). http://arxiv.org/abs/1306.1264
Ayday, E., Raisaro, J.L., Hengartner, U., Molyneaux, A., Hubaux, J.P.: Privacy-preserving processing of raw genomic data. EPFL-REPORT-187573 (2013). https://infoscience.epfl.ch/record/187573
Ayday, E., Raisaro, J.L., Hubaux, J.P.: Personal use of the genomic data: privacy vs. storage cost. In: Proceedings of IEEE Global Communications Conference, Exhibition and Industry Forum (Globecom) (2013)
Ayday, E., Raisaro, J.L., Hubaux, J.P.: Privacy-enhancing technologies for medical tests using genomic data (short paper). In: 20th Annual Network and Distributed System Security Symposium (NDSS) (2013)
Ayday, E., Raisaro, J.L., McLaren, P.J., Fellay, J., Hubaux, J.P.: Privacy-preserving computation of disease risk by using genomic, clinical, and environmental data. In: Proceedings of USENIX Security Workshop on Health Information Technologies (HealthTech) (2013)
Baldi, P., Baronio, R., De Cristofaro, E., Gasti, P., Tsudik, G.: Countering GATTACA: efficient and secure testing of fully-sequenced human genomes. In: Proceedings of ACM CCS ’11, pp. 691–702 (2011)
Bernstein, D.J.: The Salsa20 family of stream ciphers. In: Robshaw, M., Billet, O. (eds.) New Stream Cipher Designs. LNCS, vol. 4986, pp. 84–97. Springer, Heidelberg (2008). http://dx.doi.org/10.1007/978-3-540-68351-3_8
Chen, Y., Peng, B., Wang, X., Tang, H.: Large-scale privacy-preserving mapping of human genomic sequences on hybrid clouds. In: NDSS’12: Proceeding of the 19th Network and Distributed System Security Symposium (2012)
Fienberg, S.E., Slavkovic, A., Uhler, C.: Privacy preserving GWAS data sharing. In: Proceedings of the IEEE ICDMW ’11, December 2011
Gymrek, M., McGuire, A.L., Golan, D., Halperin, E., Erlich, Y.: Identifying personal genomes by surname inference. Science 339(6117), 321–324 (2013)
Jha, S., Kruger, L., Shmatikov, V.: Towards practical privacy for genomic computation. In: Proceedings of the 2008 IEEE Symposium on Security and Privacy, pp. 216–230 (2008)
Popa, R.A., Redfield, C.M.S., Zeldovich, N., Balakrishnan, H.: CryptDB: protecting confidentiality with encrypted query processing. In: Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (2011)
Troncoso-Pastoriza, J.R., Katzenbeisser, S., Celik, M.: Privacy preserving error resilient DNA searching through oblivious automata. In: CCS ’07: Proceedings of the 14th ACM Conference on Computer and Communications Security (2007)
Wang, R., Li, Y.F., Wang, X., Tang, H., Zhou, X.: Learning your identity and disease from research papers: information leaks in genome wide association study. In: Proceedings of ACM CCS ’09, pp. 534–544 (2009)
Zhou, X., Peng, B., Li, Y.F., Chen, Y., Tang, H., Wang, X.F.: To release or not to release: evaluating information leaks in aggregate human-genome data. In: Atluri, V., Diaz, C. (eds.) ESORICS 2011. LNCS, vol. 6879, pp. 607–627. Springer, Heidelberg (2011)
Acknowledgements
We would like to thank Jurgi Camblong, Pierre Hutter, Zhenyu Xu, Wolfgang Huber, and Lars Steinmetz for their useful comments.
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Ayday, E., Raisaro, J.L., Hengartner, U., Molyneaux, A., Hubaux, JP. (2014). Privacy-Preserving Processing of Raw Genomic Data. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W. (eds) Data Privacy Management and Autonomous Spontaneous Security. DPM SETOP 2013 2013. Lecture Notes in Computer Science(), vol 8247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54568-9_9
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