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Privacy-Preserving Secure Multiparty Computation on Electronic Medical Records for Star Exchange Topology

  • Research Article - Computer Engineering and Computer Science
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Abstract

Nowadays, a huge amount of data are available and shared in collaborative scenarios. These scenarios exist due to the need for joint computations of cooperating data owners for the purpose of making analysis and knowledge extraction. This requirement comes together with some privacy issues. One major issue is how to enable query execution, while no party is allowed to see the entire dataset (computational privacy). Thus, secure multiparty computation protocols allow a group of distrustful data owners to jointly cooperate in executing analytical queries against their data while revealing nothing about the entire dataset. In this paper, we propose a technique that enables a privacy-preserving query processing on horizontally partitioned electronic medical records among a set of hospitals, which have no desire to share their confidential data; however, they all need to cooperate to answer global queries about patients’ medical history. The proposed technique depends on a bucketization technique to reduce computational costs. It relies on a head party, which acts as a mediator between the authorized users and the cooperating parties, which are arranged in a star exchange topology. It ensures that the head party learns nothing about the sensitive data. Our experimental results prove that our technique provides a smaller computational cost and better privacy without the need for a trusted third party.

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References

  1. Wu, D.: Research on patient privacy protection for medical data in cloud computing. J. Netw. 8(11), 2678–2684 (2013)

    Google Scholar 

  2. Lee, K.H.; Lee, D.: Electronic medical records privacy preservation through k -anonymity clustering method. In: IEEE, pp. 1119–1124 (2012)

  3. Sabbeh, S.F.: Privacy preservation in the cloud: current solutions and open issues. Int. J. Comput. Trends Technol. (IJCTT). (2017). https://doi.org/10.14445/22312803/IJCTT-V51P102

    Article  Google Scholar 

  4. Zhaolong, G.; Yamaguchi, S.; Gupta, B.B.: Analysis of various security issues and challenges in cloud computing environment: a survey. In: Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security (2016)

  5. Omkar Badve, B.B.; Gupta, S.G.: Reviewing the security features in contemporary security policies and models for multiple platforms. In: Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security (2016)

  6. Sheikh, R.; Mishra, D.K.: Secure sum computation for insecure networks. In: Proceeding ICTCS ’16 Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies Article No. 102 , ACM ICTCS ’16 Proceedings of the Second International Conference on Information and Communication (2016)

  7. Sepehri, M.; Cimato, S.; Damiani, E.: Privacy-preserving query processing by multi-party computation. Comput. J. Secur. Comput. Syst. Netw. 58(10), 2195–2212 (2015)

    Google Scholar 

  8. Agrawal, R.; Evfimievski, A.; Srikant, R.: Information sharing across private databases. In: Proceedings of the 2003 ACM SIGMOD International Conference on on Management of Data, p. 86 (2003)

  9. Yao, A.C.C.: How to generate and exchange secrets. In: Proceedings of 27th Annual Symposium on Foundations of Computer Science, IEEE Computer Society (1), pp. 162–167 (1986)

  10. Lindell, Y.: A proof of security of Yao’s protocol for two-party computation. J. Cryptol. 22, 161–188 (2009)

    Article  MathSciNet  Google Scholar 

  11. Kruger, L.; Jha, S.; Goh, E.J.; Boneh, D.: Secure function evaluation with ordered binary decision diagrams. In: Proceedings of the 13th ACM Conference on Computer and Communications Security—CCS ’06, p. 410 (2006)

  12. Iliev, A.; Smith, S.W.: Small, stupid, and scalable: secure computing with faerieplay. In: The ACM Workshop on Scalable Trusted Computing, pp. 41–51 (2010)

  13. Evans, D.; Katz, J.: Faster secure two-party computation using garbled circuits. In: 20th USENIX Security Symposium (August), pp. 8–12 (2011)

  14. Jha, S.; Kruger, L.; Shmatikov, V.: Towards practical privacy for genomic computation. In: Proceedings—IEEE Symposium on Security and Privacy, pp. 216–230 (2008)

  15. Bellare, M.; Hoang, V.T.; Rogaway, P.: Foundations of garbled circuits. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security—CCS ’12, p. 784 (2012)

  16. Malkhi, D.; Nisan, N.; Pinkas, B.; Sella, Y.: Fairplay—-Secure Two-Party Computation System. USENIX Security Symposium, pp. 287–302 (2004)

  17. Mohassel, P.; Franklin, M.: Efficiency tradeoffs for malicious two-party computation. Proc. Public Key Cryptogr. Conf. 3958 LNCS, 458–473 (2006)

    MathSciNet  MATH  Google Scholar 

  18. Huang, Y.; Katz, J.; Evans, D.: Efficient secure two-party computation using symmetric cut-and-choose. Crypto 8043 LNCS(PART 2), 18–35 (2013)

    MathSciNet  MATH  Google Scholar 

  19. Woodruff, D.P.: Revisiting the efficiency of malicious two-party computation. In: Advances in Cryptology—EUROCRYPT 2007, 26th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Barcelona, Spain, May 20–24, 2007, Proceedings 4515, pp. 79–96 (2007)

  20. Goldreich, O.; Micali, S.; Wigderson, A.: How to play any mental game. In: Symposium on Theory of Computing, pp. 218–229 (1987)

  21. Beaver, D.: Efficient multiparty protocols using circuit randomization. Crypto 576(814), 420–432 (1991)

    MATH  Google Scholar 

  22. Atallah, M.; Bykova, M.; Li, J.; Frikken, K.; Topkara, M.: Private collaborative forecasting and benchmarking. In: Proceedings of the 2004 ACM Workshop on Privacy in the Electronic Society—WPES ’04, p. 103 (2004)

  23. Pullonen, P.; Bogdanov, D.; Schneider, T.: Institute of information security the design and implementation of a two-party protocol suite for Sharemind 3. CYBERNETICA Institute of Information Security, Institute of Information Security (2013)

  24. Damgård, I.; Orlandi, C.: Multiparty computation for dishonest majority: from passive to active security at low cost. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6223 LNCS, pp. 558–576 (2010)

  25. Bringer, J.; Chabanne, H.; Favre, M.; Patey, A.; Schneider, T.; Zohner, M.: GSHADE: faster privacy-preserving distance computation and biometric identification. In: Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security, pp. 187–198 (2014)

  26. Gilboa, N.: Two party RSA key generation. In: Advances in CryptologyCRYPTO’99, pp. 116–129 (1999)

  27. Naor, M.; Pinkas, B.: Oblivious polynomial evaluation. SIAM J. Comput. 35(5), 1254–1281 (2006)

    Article  MathSciNet  Google Scholar 

  28. Özarar, M.; Özgit, A.: Secure multiparty overall mean computation via oblivious polynomial evaluation. In: Proceedings of the First International Conference on Security and Networks (2008)

  29. Chang, Y.C.; Lu, C.J.: Oblivious polynomial evaluation and oblivious neural learning. Theor. Comput. Sci. 341(1–3), 39–54 (2005)

    Article  MathSciNet  Google Scholar 

  30. Luyao, L.; Zongtao, D.; Qinglong, W.: Unconditionally secure oblivious polynomial evaluation protocol. In: International Conference on Advanced Information and Communication Technology for Education (Icaicte), pp. 579–583 (2013)

  31. Rivest, R.L.; Dertouzos, M.L.: On data banks and privacy homomorphisms. In: Proceedings of IEEE Annual Symposium on Foundations of Computer Science (1978)

  32. Osadchy, M.; Pinkas, B.; Jarrous, A.; Moskovich, B.: SCiFI—a system for secure face identification. In: 2010 IEEE Symposium on Security a Privacy (2), pp. 239–254 (2010)

  33. Carter, H.; Amrutkar, C.; Dacosta, I.; Traynor, P.: For your phone only: custom protocols for efficient secure function evaluation on mobile devices. Security and Communication Networks 7(7), 1165–1176 (2014)

    Article  Google Scholar 

  34. Brickell, J.; Shmatikov, V.: Privacy-preserving graph algorithms in the semi-honest model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3788 LNCS, pp. 236–252 (2005)

  35. Hazay, C.; Lindell, Y.: Efficient protocols for set intersection and pattern matching with security against malicious and covert adversaries. J. Cryptol. 23(3), 422–456 (2010)

    Article  MathSciNet  Google Scholar 

  36. Miyaji, A.; Rahman, M.S.: Privacy-preserving data mining in presence of covert adversaries. In: Adma 2010 1(LNCS 6440), pp. 429–440 (2010)

  37. Vaidya, J.; Clifton, C.: Secure set intersection cardinality with application to association rule mining. J. Comput. Secur. 13, 593–622 (2004)

    Article  Google Scholar 

  38. Huang, K.; Tso, R.: A commutative encryption scheme based on ElGamal encryption. In: Proceedings—3rd International Conference on Information Security and Intelligent Control, ISIC 2012, pp. 156–159 (2012)

  39. Khayat, S.H.: Using commutative encryption to share a secret key idea proposed scheme description. Electrical Engineering, pp. 1–6 (2008)

  40. Ishai, Y.; Kilian, J.; Nissim, K.; Petrank, E.: Extending oblivious transfer efficiently. In: Advances in Cryptology-CRYPTO 2003, pp. 145–161 (2003)

  41. Freedman, M.J.; Nissim, K.; Pinkas, B.: Efficient private matching and set intersection. Eurocrypto 2004 (i), 1–19 (2004)

  42. Sang, Y.; Shen, H.; Tan, Y.; Xiong, N.: Efficient protocols for privacy preserving matching against distributed datasets. In: Proceedings of Information and Communications Security, vol. 4307, pp. 210–227 (2006)

  43. Kissner, L.; Song, D.X.: Privacy-preserving set operations. Crypto 2005 3621 (February 2005), pp. 241–257 (2005)

  44. Li, R.; Wu, C.K.: Co-operative private equality test. Int. J. Netw. Secur. 1(3), 149–153 (2005)

    Google Scholar 

  45. Sepehri, M.: Privacy-preserving query processing by multi-party computation and encrypted data outsourcing. Ph.D. thesis (2012)

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Authors and Affiliations

  1. Information Technology Department, Faculty of Computers and Informatics, Benha University, Benha, Egypt

    Ahmed M. Tawfik

  2. Information Systems Department, Faculty of Computers and Information Technology, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

    Sahar F. Sabbeh

  3. Information Systems Department, Faculty of Computers and Informatics, Benha University, Benha, Egypt

    Sahar F. Sabbeh & Tarek EL-Shishtawy

Authors
  1. Ahmed M. Tawfik
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  2. Sahar F. Sabbeh
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  3. Tarek EL-Shishtawy
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Correspondence to Ahmed M. Tawfik.

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Tawfik, A.M., Sabbeh, S.F. & EL-Shishtawy, T. Privacy-Preserving Secure Multiparty Computation on Electronic Medical Records for Star Exchange Topology. Arab J Sci Eng 43, 7747–7756 (2018). https://doi.org/10.1007/s13369-018-3122-5

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  • DOI: https://doi.org/10.1007/s13369-018-3122-5

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