Skip to main content

Designing a Bit-Based Model to Accelerate Query Processing Over Encrypted Databases in Cloud

  • Conference paper
  • First Online:
Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications (CloudComp 2019, SmartGift 2019)

Abstract

Database users have started moving toward the use of cloud computing as a service because it provides computation and storage needs at affordable prices. However, for most of the users, the concern of privacy plays a major role as they cannot control data access once their data are outsourced, especially if the cloud provider is curious about their data. Data encryption is an effective way to solve privacy concerns, but executing queries over encrypted data is a problem that needs attention. In this research, we introduce a bit-based model to execute different relational algebra operators over encrypted databases at the cloud without decrypting the data. To encrypt data, we use the randomized encryption algorithm (AES-CBC) to provide the maximum-security level. The idea is based on classifying attributes as sensitive and non-sensitive, where only sensitive attributes are encrypted. For each sensitive attribute, the table’s owner predefines the possible partition domains on which the tuples will be encoded into bit vectors before the encryption. We store the bit vectors in an additional column in the encrypted table in the cloud. We use those bits to retrieve only part of encrypted records that are candidates for a specific query. We implemented and evaluated our model and found that the proposed model is practical and success to minimize the range of the retrieved encrypted records to less than 30% of the whole set of encrypted records in a table.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Almakdi, S., Panda, B.: Secure and efficient query processing technique for encrypted databases in cloud. In: 2019 2nd International Conference on Data Intelligence and Security (ICDIS). IEEE (2019)

    Google Scholar 

  2. Alsirhani, A., Bodorik, P., Sampalli, S.: Improving database security in cloud computing by fragmentation of data. In: 2017 International Conference on Computer and Applications (ICCA). IEEE (2017)

    Google Scholar 

  3. Cui, S., Asghar, M.R., Galbraith, S.D., Russello, G.: P-McDb: privacy-preserving search using multi-cloud encrypted databases. In: 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), pp. 334–341. IEEE, June 2017

    Google Scholar 

  4. Cash, D., et al.: Dynamic searchable encryption in very-large databases: data structures and implementation. In: NDSS 2014. The Internet Society (2014)

    Google Scholar 

  5. Cash, D., Grubbs, P., Perry, J., Ristenpart, T.: Leakage-abuse attacks against searchable encryption. In: Ray, I., Li, N., Kruegel, C. (eds.) SIGSAC 2015, pp. 668–679. ACM (2015)

    Google Scholar 

  6. Stefanov, E., Papamanthou, C., Shi, E.: Practical dynamic searchable encryption with small leakage. In: NDSS 2013, vol. 71, pp. 72–75 (2014)

    Google Scholar 

  7. Gentry, C.: Fully homomorphic encryption using ideal lattices. In: STOC, vol. 9, no. 2009, pp. 169–178, May 2009

    Google Scholar 

  8. Gentry, C., Halevi, S., Smart, Nigel P.: Fully homomorphic encryption with polylog overhead. In: Pointcheval, D., Johansson, T. (eds.) EUROCRYPT 2012. LNCS, vol. 7237, pp. 465–482. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29011-4_28

    Chapter  Google Scholar 

  9. Hacigümüş, H., Iyer, B., Li, C., Mehrotra, S.: Executing SQL over encrypted data in the database-service-provider model. In: Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, pp. 216–227. ACM (2002)

    Google Scholar 

  10. Hacigumus, V.H., Raghavendra Iyer, B., Mehrotra, S.: Query optimization in encrypted database systems. U.S. Patent No. 7,685,437, 23 Mar 2010

    Google Scholar 

  11. Hore, B., et al.: Secure multidimensional range queries over outsourced data. VLDB J. 21(3), 333–358 (2012)

    Article  Google Scholar 

  12. Hore, B., Mehrotra, S., Tsudik, G.: A privacy-preserving index for range queries. In: Proceedings of the Thirtieth International Conference on Very Large Data Bases-Volume 30. VLDB Endowment (2004)

    Google Scholar 

  13. Li, K., Zhang, W., Yang, C., Yu, N.: Security analysis on one-to-many order preserving encryption-based cloud data search. IEEE Trans. Inf. Forensics Secur. 10(9), 1918–1926 (2015)

    Article  Google Scholar 

  14. Kamara, S., Moataz, T.: SQL on structurally-encrypted databases. In: Peyrin, T., Galbraith, S. (eds.) ASIACRYPT 2018. LNCS, vol. 11272, pp. 149–180. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03326-2_6

    Chapter  Google Scholar 

  15. Li, J., Liu, Z., Chen, X., Xhafa, F., Tan, X., Wong, D.S.: L-EncDB: a lightweight framework for privacy-preserving data queries in cloud computing. Knowl.-Based Syst. 79, 18–26 (2015)

    Article  Google Scholar 

  16. Liu, D., Wang, S.: Nonlinear order preserving index for encrypted database query in service cloud environments. Concurrency Comput. Pract. Exp. 25(13), 1967–1984 (2013)

    Article  Google Scholar 

  17. Liu, G., Yang, G., Wang, H., Xiang, Y., Dai, H.: A novel secure scheme for supporting complex SQL queries over encrypted databases in cloud computing. Secur. Commun. Netw. 2018, 15 (2018)

    Google Scholar 

  18. Liu, X., Choo, K.K.R., Deng, R.H., Lu, R., Weng, J.: Efficient and privacy-preserving outsourced calculation of rational numbers. IEEE Trans. Dependable Secure Comput. 15(1), 27–39 (2018)

    Article  Google Scholar 

  19. Liu, Z., Chen, X., Yang, J., Jia, C., You, I.: New order preserving encryption model for outsourced databases in cloud environments. J. Netw. Comput. Appl. 59, 198–207 (2016)

    Article  Google Scholar 

  20. Asghar, M.R., Russello, G., Crispo, B., Ion, M.: Supporting complex queries and access policies for multi-user encrypted databases. In: Juels, A., Parno, B. (eds.) CCSW 2013, pp. 77–88. ACM (2013)

    Google Scholar 

  21. Omran, O.M.: Data partitioning methods to process queries on encrypted databases on the cloud. Theses and Dissertations. 1580 (2016)

    Google Scholar 

  22. Poddar, R., Boelter, T., Popa, R.A.: Arx: A strongly encrypted database system. IACR Cryptology ePrint Archive 2016, 591 (2016)

    Google Scholar 

  23. Popa, R.A., et al.: CryptDB: processing queries on an encrypted database. Commun. ACM 55(9), 103–111 (2012)

    Article  Google Scholar 

  24. Agrawal, R., Kiernan, J., Srikant, R., Xu, Y.R.: Order preserving encryption for numeric data. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 2004), Paris, France, June 2004, pp. 563–574. ACM (2004)

    Google Scholar 

  25. Raybourn, T., Lee, J.K., Kresman, R.: On privacy preserving encrypted data stores. In: Park, James J.(Jong Hyuk), Ng, J.K.-Y., Jeong, H.Y., Waluyo, B. (eds.) Multimedia and Ubiquitous Engineering. LNEE, vol. 240, pp. 219–226. Springer, Dordrecht (2013). https://doi.org/10.1007/978-94-007-6738-6_28

    Chapter  Google Scholar 

  26. Raybourn, T.: Bucketization techniques for encrypted databases: quantifying the impact of query distributions. Dissertation, Bowling Green State University (2013)

    Google Scholar 

  27. Shastri, S., Kresman, R., Lee, J.K.: An improved algorithm for querying encrypted data in the cloud. 2015 Fifth International Conference on Communication Systems and Network Technologies (CSNT). IEEE (2015)

    Google Scholar 

  28. Tu, S., et al.: Processing analytical queries over encrypted data. In: Proceedings of the VLDB Endowment. vol. 6. no. 5 (2013)

    Article  Google Scholar 

  29. Wang, J., et al.: Bucket-based authentication for outsourced databases. Concurrency Comput. Pract. Exp. 22(9), 1160–1180 (2010)

    Google Scholar 

  30. Wang, W., Hu, Y., Chen, L., Huang, X., Sunar, B.: Exploring the feasibility of fully homomorphic encryption. IEEE Trans. Comput. 64(3), 698–706 (2015)

    Article  MathSciNet  Google Scholar 

  31. Wong, W.K., et al.: Secure query processing with data interoperability in a cloud database environment. In: Proceedings of the 2014 ACM SIGMOD international conference on Management of data. ACM (2014)

    Google Scholar 

  32. Zhang, Y., Katz, J., Papamanthou, C.: All your queries are belong to us: the power of file-injection attacks on searchable encryption. In: USENIX Security 2016, pp. 707–720. USENIX Association (2016)

    Google Scholar 

  33. Harkins, D.: Synthetic initialization vector (siv) authenticated encryption using the advanced encryption standard (aes) (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sultan Almakdi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Almakdi, S., Panda, B. (2020). Designing a Bit-Based Model to Accelerate Query Processing Over Encrypted Databases in Cloud. In: Zhang, X., Liu, G., Qiu, M., Xiang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-48513-9_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-48512-2

  • Online ISBN: 978-3-030-48513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics