A New Privacy-Preserving Searching Model on Blockchain

  • Meiqi He
  • Gongxian Zeng
  • Jun Zhang
  • Linru Zhang
  • Yuechen Chen
  • SiuMing YiuEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11396)


It will be convenient for users if there is a market place that sells similar products provided by different suppliers. In physical world, this may not be easy, in particular, if the suppliers are from different regions or countries. On the other hand, this is more feasible in the virtual world. The Global Big Data Exchange in Guiyang, China, which provides a market place for traders to buy and sell data, is a typical example. However, these virtual market places are owned by third parties. The security/privacy is a concern in addition to the expensive service charges. In this work, we propose a new privacy-preserving searching model on blockchain which enables a decentralized and secure virtual search-and-match market place. The core technical contribution is a new searchable encryption scheme for blockchain. We adopt the similarity preserving hash and leverage smart contracts to protect the system from the forgery attack and double-rewarding attack. We formally prove the security and privacy of our protocol, and evaluate our scheme on the private net of Ethereum platform. Our experimental results show that our protocol can work efficiently.


Security and privacy Privacy-preserving searching Blockchain 



This project is partially supported by a RGC Project (CityU C1008-16G) funded by the HK Government.


  1. 1.
    Breitinger, F., Astebøl, K.P., Baier, H., Busch, C.: mvHash-B-A new approach for similarity preserving hashing. In: 2013 Seventh International Conference on IT Security Incident Management and it Forensics (IMF), pp. 33–44. IEEE (2013)Google Scholar
  2. 2.
    Breitinger, F., Baier, H.: Similarity preserving hashing: eligible properties and a new algorithm mrsh-v2. In: Rogers, M., Seigfried-Spellar, K.C. (eds.) ICDF2C 2012. LNICST, vol. 114, pp. 167–182. Springer, Heidelberg (2013). Scholar
  3. 3.
    Breitinger, F., Baier, H., Beckingham, J.: Security and implementation analysis of the similarity digest sdhash. In: First International Baltic Conference on Network Security & Forensics (nesefo) (2012)Google Scholar
  4. 4.
    Buterin, V.: Ethereum: a next-generation smart contract and decentralized application platform (2014).
  5. 5.
    Cash, D., Grubbs, P., Perry, J., Ristenpart, T.: Leakage-abuse attacks against searchable encryption. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, pp. 668–679. ACM (2015)Google Scholar
  6. 6.
    Cash, D., et al.: Dynamic searchable encryption in very-large databases: data structures and implementation. In: NDSS, vol. 14, pp. 23–26 (2014)Google Scholar
  7. 7.
    Curtmola, R., Garay, J., Kamara, S., Ostrovsky, R.: Searchable symmetric encryption: improved definitions and efficient constructions. J. Comput. Secur. 19(5), 895–934 (2011)CrossRefGoogle Scholar
  8. 8.
    Decker, C., Wattenhofer, R.: A fast and scalable payment network with bitcoin duplex micropayment channels. In: Pelc, A., Schwarzmann, A.A. (eds.) SSS 2015. LNCS, vol. 9212, pp. 3–18. Springer, Cham (2015). Scholar
  9. 9.
    Delmolino, K., Arnett, M., Kosba, A.E., Miller, A., Shi, E.: Step by step towards creating a safe smart contract: lessons and insights from a cryptocurrency lab. IACR Cryptology ePrint Archive, p. 460 (2015)Google Scholar
  10. 10.
    Goh, E.J., et al.: Secure indexes. IACR Cryptology ePrint Archive, p. 216 (2003)Google Scholar
  11. 11.
    Grubbs, P., McPherson, R., Naveed, M., Ristenpart, T., Shmatikov, V.: Breaking web applications built on top of encrypted data. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 1353–1364. ACM (2016)Google Scholar
  12. 12.
    Heilman, E., Baldimtsi, F., Goldberg, S.: Blindly signed contracts: anonymous on-blockchain and off-blockchain bitcoin transactions. In: Clark, J., Meiklejohn, S., Ryan, P.Y.A., Wallach, D., Brenner, M., Rohloff, K. (eds.) FC 2016. LNCS, vol. 9604, pp. 43–60. Springer, Heidelberg (2016). Scholar
  13. 13.
    Kamara, S., Papamanthou, C., Roeder, T.: Dynamic searchable symmetric encryption. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, pp. 965–976. ACM (2012)Google Scholar
  14. 14.
    Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008)Google Scholar
  15. 15.
    Oliver, J., Cheng, C., Chen, Y.: TLSH-a locality sensitive hash. In: 2013 Fourth Cybercrime and Trustworthy Computing Workshop (CTC), pp. 7–13. IEEE (2013)Google Scholar
  16. 16.
    Oliver, J., Forman, S., Cheng, C.: Using randomization to attack similarity digests. In: Batten, L., Li, G., Niu, W., Warren, M. (eds.) ATIS 2014. CCIS, vol. 490, pp. 199–210. Springer, Heidelberg (2014). Scholar
  17. 17.
    Poon, J., Dryja, T.: The bitcoin lightning network (2015)Google Scholar
  18. 18.
    Popa, R.A., Zeldovich, N.: Multi-key searchable encryption. IACR Cryptology ePrint Archive, p. 508 (2013)Google Scholar
  19. 19.
    Popa, R.A., et al.: Building web applications on top of encrypted data using Mylar. In: NSDI, pp. 157–172 (2014)Google Scholar
  20. 20.
    Song, D.X., Wagner, D., Perrig, A.: Practical techniques for searches on encrypted data. In: 2000 IEEE Symposium on Security and Privacy, S&P 2000, Proceedings, pp. 44–55. IEEE (2000)Google Scholar
  21. 21.
    Van Rompay, C., Molva, R., Önen, M.: A leakage-abuse attack against multi-user searchable encryption. Proc. Priv. Enhancing Technol. 2017(3), 168–178 (2017)CrossRefGoogle Scholar
  22. 22.
    Van Rompay, C., Molva, R., Önen, M.: Secure and scalable multi-user searchable encryption (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Meiqi He
    • 1
  • Gongxian Zeng
    • 1
  • Jun Zhang
    • 1
  • Linru Zhang
    • 1
  • Yuechen Chen
    • 1
  • SiuMing Yiu
    • 1
    Email author
  1. 1.The University of Hong KongPok Fu LamHong Kong

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