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Encrypted SQL Arithmetic Functions Processing for Secure Cloud Database

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Security, Privacy, and Applied Cryptography Engineering (SPACE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 13162))

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Abstract

With the growing opportunities in cloud computing, different types of databases are used for storing and managing heterogeneous data in the cloud. However, several reported data breaches show that data security promises as per cloud agreement are not adequate to move critical data to cloud. Homomorphic Encryption (HE) emerges as a security solution in this regard. However, it is a non-trivial task to realize any algorithm in circuit-based representation to be implemented in homomorphic domain. Moreover, existing encrypted databases are with limited features and still not fully able to perform SQL query processing along with complex mathematical operations in encrypted domain without any need of intermediate decryption. In this work, we explore implementing the encrypted counterparts of a few complex transaction-SQL related mathematical functions like ABS(), CEILING(), FLOOR(), SIGN(), SQUARE(), POWER(), and SQRT(), which are heavily used in cloud database queries. We have evaluated these mathematical operators without any intermediate decryption, considering the support of underlying fully homomorphic encryption (FHE). Though the usage of underlying FHE scheme incurs some performance bottleneck, our proposed designs are flexible enough to be realized on any leveled homomorphic encryption (LHE) scheme for performance improvement. Experimental results show FHE encrypted SQL conditional SELECT operations with complex mathematical functions can be performed within 48 min on a single processor for a dataset of 768 rows with 9 columns, and each data size of 16-bit. Performance can be further improved by suitable implementation platform translation from CPU to GPU or with the restrictions of leveled fully homomorphic encryption.

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References

  1. Mai, P.T.A., Nurminen, J.K., Francesco, M.D.: Cloud databases for Internet-of-Things data. In: Proceedings of the IEEE International Conference on Internet of Things (iThings) (2014)

    Google Scholar 

  2. Bradford contel 7 most infamous cloud security breaches (2018). https://blog.storagecraft.com/7-infamous-cloud-security-breaches/

  3. Nie, X., Yang, L.T., Feng, J., Zhang, S.: Differentially private tensor train decomposition in edge-cloud computing for SDN-based internet of things. IEEE Internet Things J. 7, 5695–5705 (2020)

    Article  Google Scholar 

  4. Gentry, C.: A fully homomorphic encryption scheme, in Ph.D. Dissertation, Stanford, CA, USA. Advisor(s) Boneh, D.: AAI3382729 (2009)

    Google Scholar 

  5. Acar, A., Aksu, H., Uluagac, A.S., Conti, M.: A Surveyon homomorphic encryption schemes: theory and implementation. arXiv:1704.03578v2 [cs.CR] (2017)

  6. Vinayagamurthy, D., Gribov, A., Gorbunov, S.: StealthDB: a scalable encrypted database with full SQL query support. arXiv:1711.02279v2, [cs.CR] (2019)

  7. Egorov, M., Wilkison, M.: Zerodb white paper. CoRR absarXiv : 1602.07168

    Google Scholar 

  8. Popa, R.A., Redfield, C.M.S., Zeldovich, N., Balakrishnan, H.: CryptDB: protecting confidentiality with encrypted query processing. In: Proceedings of the 23rd ACM Symposium on Operating System Principles, pp. 85–100 (2011)

    Google Scholar 

  9. Kumarage, H., Khalil, I., Alabdulatif, A., Tari, Z., Yi, X.: Secure data analytics for cloud-integrated Internet of Things applications. IEEE Cloud Comput. 3(2), 46–56 (2016)

    Article  Google Scholar 

  10. Always encrypted. https://www.cs.purdue.edu/homes/csjgwang/cloudb/EncrptedSQLSIGMOD20.pdf

  11. Rivest, R.L., Shamir, A., Adleman, L.: A method for obtaining digital signatures and public-key cryptosystem. In: Proceedings of the Communication. ACM, pp. 120–126 (1978)

    Google Scholar 

  12. Gamal, T.: A public key cryptosystem and a signature scheme based on discrete logarithms. Inf. IEEE Trans. 31(4), 469–472 (1985)

    Article  MathSciNet  Google Scholar 

  13. 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). https://doi.org/10.1007/3-540-48910-X_16

    Chapter  Google Scholar 

  14. Boneh, D., Goh, E.-J., Nissim, K.: Evaluating 2-DNF formulas on ciphertexts. In: Kilian, J. (ed.) TCC 2005. LNCS, vol. 3378, pp. 325–341. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-30576-7_18

    Chapter  Google Scholar 

  15. Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) fully homo-morphic encryption without bootstrapping. In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (ITCS 2012), pp. 309–325. ACM, NewYork (2012)

    Google Scholar 

  16. Grubbs, P., Ristenpart, T., Shmatikov, V.: Why your encrypted database is not secure. HotOS 2017, 162–168 (2017)

    Article  Google Scholar 

  17. Mathematical functions(transact-sql). https://docs.microsoft.com/en-us/sql/t-sql/functions/mathematical-functions-transact-sql?view=sql-server-ver15

  18. Gentry, C.: Computing arbitrary functions of encrypted data. Commun. ACM 53(3), 97–105 (2010)

    Article  Google Scholar 

  19. Chatterjee, A., Aung, K.M.M.: Fully homomorphic encryption in real world application (2019)

    Google Scholar 

  20. Rass, S., Slamanig, D.: Cryptography for Security and Privacy in Cloud Computing. Artech House Inc., Norwood (2013)

    Google Scholar 

  21. Chatterjee, A., Sengupta, I.: Translating algorithms to handle fully homomorphic encrypted data on the cloud. IEEE Trans. Cloud Comput. 6(1), 287–300 (2018)

    Article  Google Scholar 

  22. Ghulam, A.: Top 5 databases to store data of IoT applications (2021). https://iot4beginners.com/top-5-databases-to-store-iot-data/

  23. Influxdb design insights and tradeoffs. https://docs.influxdata.com/influxdb/v1.8/concepts/insights_tradeoffs/

  24. Compare cratedb. https://crate.io/cratedb-comparison/cratedb-vs-mongodb/

  25. RethinkDB: Rethinkdb https://rethinkdb.com/faq/

  26. Xue, K., Li, S., Hong, J., Xue, Y., Yu, P., Hong, N.: Two-cloud secure database for numeric-related SQL range queries with privacy preserving. IEEE Trans. Inf. Forensics Secur. 12(7), 1596–1608 (2017)

    Article  Google Scholar 

  27. Xu, C., Chen, J., Wu, W., Feng, Y.: Homomorphically encrypted arithmetic operations over the integer ring, pp. 167–181 (2016)

    Google Scholar 

  28. Built-in mathematical SQL functions. https://www.sqlite.org/langmathfunc.html

  29. Chillotti, I., Gama, N., Georgieva, M., Izabachne, M.: Faster fully homomorphic encryption : bootstrapping [1] in less than 0.1 seconds. Cryptology ePrint Archive Report 2016/870 (2016). https://eprint.iacr.org/2016/870

  30. Shift-and-add multiplication. https://users.utcluj.ro/baruch/book_ssce/SSCE-Shift-Mult.pdf

  31. Gosh, A., Chatterjee, A.: Practical performance improvement of domain aware encrypted computing. In: Proceedings of the ICMC (2021). Accepted

    Google Scholar 

  32. Jena, A., Panda, S.K.: Revision of various square-root algorithms for efficient VLSI signal processing applications. Proc. MCSP 2016, 38–41 (2016)

    Google Scholar 

  33. Pima indians diabetes database. https://www.kaggle.com/uciml/pima-indians-diabetes-database

  34. NuFHE. A GPU implementation of fully homomorphic encryption on torus. https://github.com/nucypher/nufhe

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Authors and Affiliations

  1. Indian Instutite of Technology Kharagpur, Kharagpur, India

    Tanusree Parbat & Ayantika Chatterjee

Authors
  1. Tanusree Parbat
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  2. Ayantika Chatterjee
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Editor information

Editors and Affiliations

  1. Radboud University, Nijmegen, The Netherlands

    Lejla Batina

  2. TU Delft, Delft, The Netherlands

    Stjepan Picek

  3. Indian Institute of Technology Kharagpur, Kharagpur, India

    Mainack Mondal

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Parbat, T., Chatterjee, A. (2022). Encrypted SQL Arithmetic Functions Processing for Secure Cloud Database. In: Batina, L., Picek, S., Mondal, M. (eds) Security, Privacy, and Applied Cryptography Engineering. SPACE 2021. Lecture Notes in Computer Science(), vol 13162. Springer, Cham. https://doi.org/10.1007/978-3-030-95085-9_11

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  • DOI: https://doi.org/10.1007/978-3-030-95085-9_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95084-2

  • Online ISBN: 978-3-030-95085-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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