Data Integrity Verification in Column-Oriented NoSQL Databases

  • Grisha WeintraubEmail author
  • Ehud GudesEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10980)


Data integrity in cloud databases is a topic that has received a much of attention from the research community. However, existing solutions mainly focus on the cloud providers that store data in relational databases, whereas nowadays many cloud providers store data in non-relational databases as well. In this paper, we focus on the particular family of non-relational databases—column-oriented stores, and present a protocol that will allow cloud users to verify the integrity of their data that resides on cloud databases of this type. We like our solution to be easily integrated with the existing real-world systems and therefore assume that we cannot modify the cloud; our protocol is implemented solely on the client side. We have implemented a prototype of our solution, that uses Cloud BigTable as a cloud database, and have evaluated its performance and correctness.


Data integrity Database outsourcing NoSQL 


  1. 1.
    Leavitt, N.: Will NoSQL databases live up to their promise? Computer 43(2), 12–14 (2010)CrossRefGoogle Scholar
  2. 2.
    Cattell, R.: Scalable SQL and NoSQL data stores. ACM SIGMOD Rec. 39(4), 12–27 (2011)CrossRefGoogle Scholar
  3. 3.
    Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Gruber, R.E.: Bigtable: a distributed storage system for structured data. ACM Trans. Comput. Syst. (TOCS) 26(2), 4 (2008)CrossRefGoogle Scholar
  4. 4.
    Weintraub, G.: Dynamo and BigTable - review and comparison. In: Proceedings of the 28th Convention of the Electrical & Electronics Engineers in Israel, pp. 1–5. IEEE (2014)Google Scholar
  5. 5.
    Hacigms, H., Iyer, B., Mehrotra, S.: Providing database as a service. In: Proceedings of the 18th International Conference on Data Engineering, pp. 29–38. IEEE (2002)Google Scholar
  6. 6.
    Merkle, R.C.: A certified digital signature. In: Brassard, G. (ed.) CRYPTO 1989. LNCS, vol. 435, pp. 218–238. Springer, New York (1990). Scholar
  7. 7.
    Devanbu, P., Gertz, M., Martel, C., Stubblebine, S.G.: Authentic data publication over the internet. J. Comput. Secur. 11(3), 291–314 (2003)CrossRefGoogle Scholar
  8. 8.
    Li, F., Hadjieleftheriou, M., Kollios, G., Reyzin, L.: Dynamic authenticated index structures for outsourced databases. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, pp. 121–132. ACM (2006)Google Scholar
  9. 9.
    Yang, Y., Papadias, D., Papadopoulos, S., Kalnis, P.: Authenticated join processing in outsourced databases. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp. 5–18. ACM (2009)Google Scholar
  10. 10.
    Li, F., Hadjieleftheriou, M., Kollios, G., Reyzin, L.: Authenticated index structures for aggregation queries. ACM Trans. Inf. Syst. Secur. (TISSEC) 13(4), 32 (2010)CrossRefGoogle Scholar
  11. 11.
    Wei, W., Yu, T.: Integrity assurance for outsourced databases without dbms modification. In: Atluri, V., Pernul, G. (eds.) DBSec 2014. LNCS, vol. 8566, pp. 1–16. Springer, Heidelberg (2014). Scholar
  12. 12.
    Mykletun, E., Narasimha, M., Tsudik, G.: Authentication and integrity in outsourced databases. ACM Trans. Storage (TOS) 2(2), 107–138 (2006)CrossRefGoogle Scholar
  13. 13.
    Narasimha, M., Tsudik, G.: DSAC: integrity for outsourced databases with signature aggregation and chaining. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 235–236. ACM (2005)Google Scholar
  14. 14.
    Xie, M., Wang, H., Yin, J., Meng, X.: Integrity auditing of outsourced data. In: Proceedings of the 33rd International Conference on Very Large Data Bases, pp. 782–793. VLDB Endowment (2007)Google Scholar
  15. 15.
    Wang, H., Yin, J., Perng, C.S., Yu, P.S.: Dual encryption for query integrity assurance. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp. 863–872. ACM (2008)Google Scholar
  16. 16.
    Wei, W., Yu, T., Xue, R.: iBigTable: practical data integrity for bigtable in public cloud. In: Proceedings of the Third ACM Conference on Data and Application Security and Privacy, pp. 341–352. ACM (2013)Google Scholar
  17. 17.
    Rivest, R.L., Shamir, A., Adleman, L.: A method for obtaining digital signatures and public-key cryptosystems. Commun. ACM 21(2), 120–126 (1978)MathSciNetCrossRefGoogle Scholar
  18. 18.
    Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)CrossRefGoogle Scholar
  19. 19.
    Mitzenmacher, M.: Compressed bloom filters. IEEE/ACM Trans. Network. (TON) 10(5), 604–612 (2002)CrossRefGoogle Scholar
  20. 20.
    Secure Hash Standard: FIPS Publication 180–2. National Institute of Standards and Technology (NIST) (2002)Google Scholar
  21. 21.
    Doan, A., Ramakrishnan, R., Halevy, A.Y.: Crowdsourcing systems on the world-wide web. Commun. ACM 54(4), 86–96 (2011)CrossRefGoogle Scholar
  22. 22.
    Von Ahn, L., Dabbish, L.: Labeling images with a computer game. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 319–326. ACM (2004)Google Scholar
  23. 23.
    Pub, NIST FIPS: 197: Advanced encryption standard (AES). Federal Information Processing Standards Publication 197, 441-0311 (2001)Google Scholar
  24. 24.
    Krawczyk, H., Canetti, R., Bellare, M.: HMAC: Keyed-hashing for message authentication (1997)Google Scholar
  25. 25.
    Atikoglu, B., Xu, Y., Frachtenberg, E., Jiang, S., Paleczny, M.: Workload analysis of a large-scale key-value store. ACM SIGMETRICS Perform. Eval. Rev. 40(1), 53–64 (2012)CrossRefGoogle Scholar
  26. 26.
    Cooper, B.F., Silberstein, A., Tam, E., Ramakrishnan, R., Sears, R.: Benchmarking cloud serving systems with YCSB. In: Proceedings of the 1st ACM Symposium on Cloud Computing, pp. 143–154. ACM, June 2010Google Scholar
  27. 27.
    Weintraub, G., Gudes, E.: Crowdsourced data integrity verification for key-value stores in the cloud. In: Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 498–503. IEEE Press (2017)Google Scholar
  28. 28.

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Department of Mathematics and Computer ScienceThe Open UniversityRaananaIsrael
  2. 2.Department of Computer ScienceBen-Gurion University of the NegevBeer-ShevaIsrael

Personalised recommendations