Abstract
Genomics plays an especial role in our daily lives. Genomic data, however, are highly-sensitive and thus normally stored in repositories with strict access control insurance. This severely restricts the associated processing on genomic data, in which multiple institutes holding their own data hope to conduct specific computation on the entire dataset. Accordingly, researchers attempt to propose methods to enable secure computation on genomic data among multiple parties. Nevertheless, most of the existing solutions fall short in efficiency, security or scalability.
In this paper, we focus on providing a secure and practical solution to perform similar patient query on distributed Electronic Health Records (EHR) databases with genomic data. To achieve this, we propose a privacy-preserving framework to execute similar patient query on genomic data owned by distributed owners in a server-aided setting. Specifically, we apply multi-key homomorphic encryption to the proposed framework, where each data owner performs queries on its local EHR database, encrypts query results with its unique public key, and sends them to the servers for further secure edit-distance computation on genomic data encrypted under multiple keys. Security and performance analysis show that our system achieves satisfactory efficiency, scalability, and flexibility while protecting the privacy of each data contributor.
Supported by National Natural Science Foundation of China (No. 61702218, 61672262), Shandong Provincial Key Research and Development Project (No. 2019GGX101028, 2018CXGC0706, 2016GGX101001), Shandong Province Higher Educational Science and Technology Program (No. J18KA349), Natural Science Foundation of Shandong Province (No. ZR2014JL042, ZR2014FL011, ZR2015FL023), Project of Independent Cultivated Innovation Team of Jinan City (No. 2018GXRC002), Doctoral Program of University of Jinan (No.160100224), and Science and Technology Program of University of Jinan (No. XKY1709).
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References
Aziz, M.M.A., Alhadidi, D., Mohammed, N.: Secure approximation of edit distance on genomic data. BMC Med. Genomics 10(2), 41 (2017)
Andoni, A., Onak, K.: Approximating edit distance in near-linear time. SIAM J. Comput. 41(6), 1635–1648 (2012)
Asharov, G., Halevi, S., Lindell, Y., Rabin, T.: Privacy-preserving search of similar patients in genomic data. Proc. Priv. Enhancing Technol. 2018(4), 104–124 (2018)
Aziz, A., Momin, Md., Hasan, M.Z., Mohammed, N., Alhadidi, D.: Secure and efficient multiparty computation on genomic data. In: Proceedings of the 20th International Database Engineering & Applications Symposium, pp. 278–283. ACM (2016)
Bresson, E., Catalano, D., Pointcheval, D.: A simple public-key cryptosystem with a double trapdoor decryption mechanism and its applications. In: Laih, C.-S. (ed.) ASIACRYPT 2003. LNCS, vol. 2894, pp. 37–54. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-40061-5_3
Heather, J.M., Chain, B.: The sequence of sequencers: the history of sequencing DNA. Genomics 107(1), 1–8 (2016)
Jurafsky, D.: Speech & Language Processing. Pearson Education (2000)
Paillier, P.: Public-key cryptosystems based on composite degree residuosity classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-48910-X_16
Peter, A., Tews, E., Katzenbeisser, S.: Efficiently outsourcing multiparty computation under multiple keys. IEEE Trans. Inf. Forensics Secur. 8(12), 2046–2058 (2013)
Venter, J.C., et al.: The sequence of the human genome. Science 291(5507), 1304–1351 (2001)
Wagner, R.A., Fischer, M.J.: The string-to-string correction problem. J. ACM (JACM) 21(1), 168–173 (1974)
Wang, X.S., Huang, Y., Zhao, Y., Tang, H., Wang, X., Bu, D.: Efficient genome-wide, privacy-preserving similar patient query based on private edit distance. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, pp. 492–503. ACM (2015)
Wicks, P., et al.: Sharing health data for better outcomes on patientslikeme. J. Med. Internet Res. 12(2), e19 (2010)
Acknowledgments
Supported by National Natural Science Foundation of China (No. 61702218, 61672262), Shandong Provincial Key Research and Development Project (No. 2019GGX101028, 2018CXGC0706), Shandong Province Higher Educational Science and Technology Program (No. J18KA349), Project of Independent Cultivated Innovation Team of Jinan City (No. 2018GXRC002).
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Zhao, C., Zhao, S., Zhang, B., Jing, S., Chen, Z., Zhao, M. (2019). Towards Secure Computation of Similar Patient Query on Genomic Data Under Multiple Keys. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11983. Springer, Cham. https://doi.org/10.1007/978-3-030-37352-8_24
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DOI: https://doi.org/10.1007/978-3-030-37352-8_24
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