Skip to main content

2019 | OriginalPaper | Buchkapitel

Towards Secure Computation of Similar Patient Query on Genomic Data Under Multiple Keys

verfasst von : Chuan Zhao, Shengnan Zhao, Bo Zhang, Shan Jing, Zhenxiang Chen, Minghao Zhao

Erschienen in: Cyberspace Safety and Security

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

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.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Aziz, M.M.A., Alhadidi, D., Mohammed, N.: Secure approximation of edit distance on genomic data. BMC Med. Genomics 10(2), 41 (2017)CrossRef Aziz, M.M.A., Alhadidi, D., Mohammed, N.: Secure approximation of edit distance on genomic data. BMC Med. Genomics 10(2), 41 (2017)CrossRef
2.
Zurück zum Zitat Andoni, A., Onak, K.: Approximating edit distance in near-linear time. SIAM J. Comput. 41(6), 1635–1648 (2012)MathSciNetCrossRef Andoni, A., Onak, K.: Approximating edit distance in near-linear time. SIAM J. Comput. 41(6), 1635–1648 (2012)MathSciNetCrossRef
3.
Zurück zum Zitat 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)CrossRef 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)CrossRef
4.
Zurück zum Zitat 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) 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)
6.
Zurück zum Zitat Heather, J.M., Chain, B.: The sequence of sequencers: the history of sequencing DNA. Genomics 107(1), 1–8 (2016)CrossRef Heather, J.M., Chain, B.: The sequence of sequencers: the history of sequencing DNA. Genomics 107(1), 1–8 (2016)CrossRef
7.
Zurück zum Zitat Jurafsky, D.: Speech & Language Processing. Pearson Education (2000) Jurafsky, D.: Speech & Language Processing. Pearson Education (2000)
9.
Zurück zum Zitat Peter, A., Tews, E., Katzenbeisser, S.: Efficiently outsourcing multiparty computation under multiple keys. IEEE Trans. Inf. Forensics Secur. 8(12), 2046–2058 (2013)CrossRef Peter, A., Tews, E., Katzenbeisser, S.: Efficiently outsourcing multiparty computation under multiple keys. IEEE Trans. Inf. Forensics Secur. 8(12), 2046–2058 (2013)CrossRef
10.
Zurück zum Zitat Venter, J.C., et al.: The sequence of the human genome. Science 291(5507), 1304–1351 (2001)CrossRef Venter, J.C., et al.: The sequence of the human genome. Science 291(5507), 1304–1351 (2001)CrossRef
11.
12.
Zurück zum Zitat 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) 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)
13.
Zurück zum Zitat Wicks, P., et al.: Sharing health data for better outcomes on patientslikeme. J. Med. Internet Res. 12(2), e19 (2010)CrossRef Wicks, P., et al.: Sharing health data for better outcomes on patientslikeme. J. Med. Internet Res. 12(2), e19 (2010)CrossRef
Metadaten
Titel
Towards Secure Computation of Similar Patient Query on Genomic Data Under Multiple Keys
verfasst von
Chuan Zhao
Shengnan Zhao
Bo Zhang
Shan Jing
Zhenxiang Chen
Minghao Zhao
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-37352-8_24