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Private Subgraph Matching Protocol

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Provable Security (ProvSec 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10592))

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Abstract

In many applications, information can be stored and managed using graph data structures, and there is a rich set of graph algorithms that can be used to solve different problems. The subgraph isomorphism problem is defined as, given two graphs G and H, whether G contains a subgraph that is isomorphic to H. The problem has been well studied for many years, and it can be used for many application areas, such as cheminformatics, pattern matching, data mining and image processing. In this paper, we present a private subgraph matching protocol, which solves a special case of the subgraph isomorphism problem. The protocol allows two parties, each holding a private graph, to jointly compute whether one graph is a subgraph of the other. During the protocol, each party learns no useful information about the graph of the other party. We prove that the protocol is secure in the semi-honest setting.

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References

  1. Ullmann, J.R.: An algorithm for subgraph isomorphism. J. ACM (JACM) 23(1), 31–42 (1976)

    Article  MathSciNet  Google Scholar 

  2. Solnon, C.: All different-based filtering for subgraph isomorphism. Artif. Intell. 174(12–13), 850–864 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  3. Cordella, L.P., Foggia, P., Sansone, C., et al.: A (sub) graph isomorphism algorithm for matching large graphs. IEEE Trans. Pattern Anal. Mach. Intell. 26(10), 1367–1372 (2004)

    Article  Google Scholar 

  4. Messmer, B.T., Bunke, H.: A new algorithm for error-tolerant subgraph isomorphism detection. IEEE Trans. Pattern Anal. Mach. Intell. 20(5), 493–504 (1998)

    Article  Google Scholar 

  5. Eppstein, D.: Subgraph isomorphism in planar graphs and related problems. In: SODA 1995, pp. 632–640 (1995)

    Google Scholar 

  6. Shang, H., Zhang, Y., Lin, X., et al.: Taming verification hardness: an efficient algorithm for testing subgraph isomorphism. Proc. VLDB Endowment 1(1), 364–375 (2008)

    Article  Google Scholar 

  7. Messmer, B.T., Bunke, H.: Efficient subgraph isomorphism detection: a decomposition approach. IEEE Trans. Knowl. Data Eng. 12(2), 307–323 (2000)

    Article  Google Scholar 

  8. Raymond, J.W., Willett, P.: Maximum common subgraph isomorphism algorithms for the matching of chemical structures. J. Comput. Aided Mol. Des. 16(7), 521–533 (2002)

    Article  Google Scholar 

  9. Bonnici, V., Giugno, R., Pulvirenti, A., et al.: A subgraph isomorphism algorithm and its application to biochemical data. BMC Bioinform. 14(7), S13 (2013)

    Article  Google Scholar 

  10. Ehrlich, H.C., Rarey, M.: Maximum common subgraph isomorphism algorithms and their applications in molecular science: a review. Wiley Interdiscip. Rev. Comput. Mol. Sci. 1(1), 68–79 (2011)

    Article  Google Scholar 

  11. Koyutrk, M., Grama, A., Szpankowski, W.: An efficient algorithm for detecting frequent subgraphs in biological networks. Bioinformatics 20(Suppl. 1), i200–i207 (2004)

    Article  Google Scholar 

  12. Artymiuk, P.J., Grindley, H.M., Poirrette, A.R., et al.: Identification of beta-sheet motifs, of psi-loops, and of patterns of amino acid residues in three-dimensional protein structures using a subgraph-isomorphism algorithm. J. Chem. Inf. Comput. Sci. 34(1), 54–62 (1994)

    Article  Google Scholar 

  13. Wong, E.K.: Model matching in robot vision by subgraph isomorphism. Pattern Recogn. 25(3), 287–303 (1992)

    Article  Google Scholar 

  14. Llads, J., Mart, E., Villanueva, J.J.: Symbol recognition by error-tolerant subgraph matching between region adjacency graphs. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1137–1143 (2001)

    Article  Google Scholar 

  15. Zhu, K., Zhang, Y., Lin, X., Zhu, G., Wang, W.: NOVA: a novel and efficient framework for finding subgraph isomorphism mappings in large graphs. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds.) DASFAA 2010. LNCS, vol. 5981, pp. 140–154. Springer, Heidelberg (2010). doi:10.1007/978-3-642-12026-8_13

    Chapter  Google Scholar 

  16. Han, W.S., Lee, J., Lee, J.H.: Turbo ISO: towards ultrafast and robust subgraph isomorphism search in large graph databases. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 337–348. ACM (2013)

    Google Scholar 

  17. Foggia, P., Sansone, C., Vento, M.: A performance comparison of five algorithms for graph isomorphism. In: Proceedings of the 3rd IAPR TC-15 Workshop on Graph-Based Representations in Pattern Recognition, pp. 188–199 (2001)

    Google Scholar 

  18. Lee, J., Han, W.S., Kasperovics, R., et al.: An in-depth comparison of subgraph isomorphism algorithms in graph databases. Proc. VLDB Endowment 6(2), 133–144 (2012). VLDB Endowment

    Article  Google Scholar 

  19. Brickell, J., Shmatikov, V.: Privacy-preserving graph algorithms in the semi-honest model. In: Roy, B. (ed.) ASIACRYPT 2005. LNCS, vol. 3788, pp. 236–252. Springer, Heidelberg (2005). doi:10.1007/11593447_13

    Chapter  Google Scholar 

  20. Cao, N., Yang, Z., Wang, C., et al.: Privacy-preserving query over encrypted graph-structured data in cloud computing. In: 2011 31st International Conference on Distributed Computing Systems (ICDCS), pp. 393–402. IEEE (2011)

    Google Scholar 

  21. Meng, X., Kamara, S., Nissim, K., et al.: GRECS: graph encryption for approximate shortest distance queries. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, pp. 504–517. ACM (2015)

    Google Scholar 

  22. Chase, M., Kamara, S.: Structured encryption and controlled disclosure. In: Abe, M. (ed.) ASIACRYPT 2010. LNCS, vol. 6477, pp. 577–594. Springer, Heidelberg (2010). doi:10.1007/978-3-642-17373-8_33

    Chapter  Google Scholar 

  23. 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). doi:10.1007/3-540-48910-X_16

    Google Scholar 

  24. Kissner, L., Song, D.: Privacy-preserving set operations. In: Shoup, V. (ed.) CRYPTO 2005. LNCS, vol. 3621, pp. 241–257. Springer, Heidelberg (2005). doi:10.1007/11535218_15

    Chapter  Google Scholar 

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Acknowledgements

This work was supported in part by the National Science and Technology Major Project under Grant No. 2013ZX03002006, the Liaoning Province Science and Technology Projects under Grant No. 2013217004, the Liaoning Province Doctor Startup Fund under Grant No. 20141012, the Fundamental Research Funds for the Central Universities under Grant Numbers N130317002, N151704002, the Shenyang Province Science and Technology Projects under Grant No. F14-231-1-08, and the National Natural Science Foundation of China under Grant Numbers 61272546, 61321491, 61402095, 61472184.

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Correspondence to Fucai Zhou .

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Xu, Z., Zhou, F., Li, Y., Xu, J., Wang, Q. (2017). Private Subgraph Matching Protocol. In: Okamoto, T., Yu, Y., Au, M., Li, Y. (eds) Provable Security. ProvSec 2017. Lecture Notes in Computer Science(), vol 10592. Springer, Cham. https://doi.org/10.1007/978-3-319-68637-0_27

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  • DOI: https://doi.org/10.1007/978-3-319-68637-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68636-3

  • Online ISBN: 978-3-319-68637-0

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