Private computation on encrypted genomic data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8895, Issue , 2015, Pages 3-27

  Lauter, Kristin ^a   López Alt, Adriana ^b   Naehrig, Michael ^a  

^a MICROSOFT RESEARCH   (United States)

^b NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CRYPTOGRAPHY; DATA PRIVACY; GENES;

GENOMIC STUDIES; GOODNESS-OF-FIT TEST; HOMOMORPHIC ENCRYPTION SCHEMES; LINKAGE DISEQUILIBRIUM; PATIENT PRIVACIES; PRIVACY INVASIONS; PRIVATE COMPUTATION; TEST FOR TRENDS;

SECURITY OF DATA;

EID: 84926666038     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-16295-9_1     Document Type: Conference Paper

References (37)

1. [ADCHT13] Ayday, E., De Cristofaro, E., Hubaux, J.-P., Tsudik, G.: The Chills and Thrills of Whole Genome Sequencing. Technical report (2013). http:// infoscience.epfl.ch/record/186866/files/survey.pdf
2. [ARH13] 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)
3. [BAFM12] Blanton, M., Atallah, M.J., Frikken, K.B., Malluhi, Q.: Secure and efficient outsourcing of sequence comparisons. In: Foresti, S., Yung, M., Martinelli, F. (eds.) ESORICS 2012. LNCS, vol. 7459, pp. 505–522. Springer, Heidelberg (2012)
4. [BCP97] Bosma, W., Cannon, J., Playoust, C.: The magma algebra system. I. The user language. J. Symbolic Comput. 24(3–4), 235–265 (1997). Computational algebra and number theory (London, 1993)
5. [BGV12] Brakerski, Z., Gentry, C., Vaikuntanathan, V.: Fully homomorphic encryption without bootstrapping. In: ITCS (2012)
6. [BLLN13] Bos, J.W., Lauter, K., Loftus, J., Naehrig, M.: Improved security for a ring-based fully homomorphic encryption scheme. In: Stam, M. (ed.) IMACC 2013. LNCS, vol. 8308, pp. 45–64. Springer, Heidelberg (2013)
7. [BLN14] Bos, J.W., Lauter, K., Naehrig, M.: Private predictive analysis on encrypted medical data. J. Biomed. Inform. 50, 234–243 (2014). MSRTR- 2013-81
8. [Bra12] Brakerski, Z.: Fully homomorphic encryption without modulus switching from classical GapSVP. In: Safavi-Naini, R., Canetti, R. (eds.) CRYPTO 2012. LNCS, vol. 7417, pp. 868–886. Springer, Heidelberg (2012)
9. [BV11a] Brakerski, Z., Vaikuntanathan, V.: Efficient fully homomorphic encryption from (standard) LWE. In: Ostrovsky, R. (ed.) FOCS, pp. 97–106. IEEE (2011)
10. [BV11b] Brakerski, Z., Vaikuntanathan, V.: Fully homomorphic Encryption from Ring-LWE and security for key dependent messages. In: Rogaway, P. (ed.) CRYPTO 2011. LNCS, vol. 6841, pp. 505–524. Springer, Heidelberg (2011)
11. [BV14] Brakerski, Z., Vaikuntanathan, V.: Lattice-based FHE as secure as PKE. In: Naor, M. (ed.) ITCS, pp. 1–12. ACM (2014)
12. [dbG] Database of Genotypes and Phenotypes (dbGaP). http://www.ncbi.nlm. nih.gov/gap/
13. [DCFT13] De Cristofaro, E., Faber, S., Tsudik, G.: Secure genomic testing with size-and position-hiding private substring matching. In: Proceedings of the 2013 ACM Workshop on Privacy in the Electronic Society (WPES 2013). ACM (2013)
14. [EBI] European Bioinformatics Institute. http://www.ebi.ac.uk/ (Accessed 30 October 2013)
15. [FSU11] Fienberg, S.E., Slavkovic, A., Uhler, C.: Privacy preserving GWAS data sharing. In: 2011 IEEE 11th International Conference on Data Mining Workshops (ICDMW), pp. 628–635. IEEE (2011)
16. [FV12] Fan, J., Vercauteren, F.: Somewhat practical fully homomorphic encryption. IACR Cryptology ePrint Archive 2012, 144 (2012)
17. [Gen09] Gentry, C.: Fully homomorphic encryption using ideal lattices. In: Mitzenmacher, M. (ed.) STOC, pp. 169–178. ACM (2009)
18. [GLN13] Graepel, T., Lauter, K., Naehrig, M.: ML confidential: machine learning on encrypted data. In: Kwon, T., Lee, M.-K., Kwon, D. (eds.) ICISC 2012. LNCS, vol. 7839, pp. 1–21. Springer, Heidelberg (2013)
19. [Glo13] Creating a global alliance to enable responsible sharing of genomic and clinical data, White Paper (2013). http://www.broadinstitute.org/files/ news/pdfs/GAWhitePaperJune3.pdf
20. [GMG+13] Gymrek, M., McGuire, A.L., Golan, D., Halperin, E., Erlich, Y.: Identifying personal genomes by surname inference. Science 339(6117), 321–324 (2013)
21. [GSW13] Gentry, C., Sahai, A., Waters, B.: Homomorphic encryption from learning with errors: conceptually-simpler, asymptotically-faster, attribute-based. In: Canetti, R., Garay, J.A. (eds.) CRYPTO 2013, Part I. LNCS, vol. 8042, pp. 75–92. Springer, Heidelberg (2013)
22. [HAHT13] Humbert, M., Ayday, E., Hubaux, J.-P., Telenti, A.: 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)
23. [ICG] International cancer genome consortium (ICGC). http://www.icgc.org
24. [IRD] International rare diseases research consortium (IRDiRC). http://www. irdirc.org
25. [Jap] DNA Data Bank Of Japan. http://www.ddbj.nig.ac.jp/
26. [JS13] Johnson, A., Shmatikov, V.: Privacy-preserving data exploration in genome-wide association studies. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1079–1087. ACM (2013)
27. [LN14a] Lepoint, T., Naehrig, M.: A comparison of the homomorphic encryption schemes FV and YASHE. In: Pointcheval, D., Vergnaud, D. (eds.) AFRICACRYPT. LNCS, vol. 8469, pp. 318–335. Springer, Heidelberg (2014)
28. [LN14b] López-Alt, A., Naehrig, M.: Large integer plaintexts in ring-based fully homomorphic encryption. In preparation (2014)
29. [LNV11] Lauter, K., Naehrig, M., Vaikuntanathan, V.: Can homomorphic encryption be practical? In: Proceedings of the 3rd ACM Cloud Computing Security Workshop, pp. 113–124. ACM (2011)
30. [LTV12] López-Alt, A., Tromer, E., Vaikuntanathan, V.: On-the-fly multiparty computation on the cloud via multikey fully homomorphic encryption. In: Karloff, H.J., Pitassi, T. (eds.) STOC, pp. 1219–1234. ACM (2012)
31. [MCC+11] McCarty, C.A., Chisholm, R.L., Chute, C.G., Kullo, I.J., Jarvik, G.P., Larson, E.B., Li, R., Masys, D.R., Ritchie, M.D., Roden, D.M., et al.: The emerge network a consortium of biorepositories linked toelectronic medical records data for conducting genomic studies. BMC Med. Genomics 4(1), 13 (2011)
32. [PH08] Park, M.Y., Hastie, T.: Penalized logistic regression for detecting gene interactions. Biostatistics 9(1), 30–50 (2008)
33. [SS11] Stehlé, D., Steinfeld, R.: Making NTRU as secure as worst-case problems over ideal lattices. In: Paterson, K.G. (ed.) EUROCRYPT 2011. LNCS, vol. 6632, pp. 27–47. Springer, Heidelberg (2011)
34. [TGP] A map of human genome variation from population-scale sequencing. Nature, 467:1061–1073. http://www.1000genomes.org
35. [vDGHV10] van Dijk, M., Gentry, C., Halevi, S., Vaikuntanathan, V.: Fully homomorphic encryption over the integers. In: Gilbert, H. (ed.) EUROCRYPT 2010. LNCS, vol. 6110, pp. 24–43. Springer, Heidelberg (2010)
36. [WLW+09] Wang, R., Li, Y.F., Wang, X.F., Tang, H., Zhou, X.: Learning your identity and disease from research papers: Information leaks in genome wide association study. In: Proceedings of the 16th ACM Conference on Computer and Communications Security, CCS 2009, pp. 534–544. ACM, New York (2009)
37. [YSK+13] Yasuda, M., Shimoyama, T., Kogure, J., Yokoyama, K., Koshiba, T.: Secure pattern matching using somewhat homomorphic encryption. In: Proceedings of the 2013 ACM Cloud Computing Security Workshop, pp. 65–76. ACM (2013)