STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Telecommunication, Switching Systems and Networks Review Article

A Practical Approach for Privacy Preserving in Cloud Computing Using Fully Homomorphic Encryption Scheme BFV and CKKS

  1. Sunita Godara Department of Computer Science and Engineering, Mugneeram Bangur Memorial University, Jodhpur
  2. Simran Choudhary Department of Computer Science and Engineering, Mugneeram Bangur Memorial University, Jodhpur

Abstract

Cloud computing is a new type of computing architecture whereby data may be accessed over the Internet along with other services linked to its scalable data centers in the cloud. The risk associated with computing is increased since it provides essential services that are typically provided to any third party, making it more difficult to enable data security, privacy, confidentiality, integrity, and authentication. To reduce security risks, most users choose to save their data in the cloud in encrypted format. Nevertheless, the cloud must first decrypt the data before it can be used for any server-side operations. This operation may result in difficult problems like cloud storage secrecy and privacy of sensitive data. In this paper homomorphic encryption (HE) is presented, which also addresses issues with data privacy and confidentiality stored on the cloud. Homomorphic encryption (HE) is a type of encryption technology that allows users to perform computations on the cipher text itself. This produces an unoriginal or encrypted output, which, when decrypted, resembles the outcome of operations performed on the plain text. There are two main types of homomorphic encryption: fully homomorphic encryption (FHE) and partial homomorphic encryption (PHE). Since FHE benefits from both additive and multiplicative homomorphism, it is thought to be more secure and effective when it comes to third-party calculations. In this paper focus is on giving a short overview of FHE, its types, and practical implementation of BFV and CKKS along with their performance analysis.

Keywords

References (18)

  1. Rivest RL, Adleman L, Dertouzos ML. On data banks and privacy homomorphisms. Foundations of secure computation. 1978 Oct 16;4(11):169-80.
  2. Gentry and D. Boneh, A fully homomorphic encryption scheme. Stanford university Stanford, Stanford University ProQuest Dissertations & Theses, 2009. vol. 20, no. 09. 3382729.
  3. Smart NP, Vercauteren F. Fully Homomorphic Encryption with Relatively Small Key and Ciphertext Sizes. Lecture Notes in Computer Science. 2010:420-443. doi:10.1007/978-3-642-13013-7_25
  4. V. Parmar, S. B. Padhar, S. N. Patel, N. I. Bhatt, and R. H. Jhaveri, “Survey of various homomorphic encryption algorithms and schemes,” International Journal of Computer Applications, vol. 91, no. 8, 2014. 26-32.
  5. Acar, H. Aksu, A. S. Uluagac, and M. Conti, “A survey on homomorphic encryption schemes: Theory and implementation,” ACM Computing Surveys (CSUR), vol. 51, no. 4, pp. 1–35, 2018.
  6. Brakerski, “Fundamentals of fully homomorphic encryption-a survey.” in Electronic Colloquium on Computational Complexity (ECCC), vol. 25, 2018, p. 125.
  7. Alloghani, M. M. Alani, D. Al-Jumeily, T. Baker, J. Mustafina, A. Hussain, and A. J. Aljaaf, “A systematic review on the status and progress of homomorphic encryption technologies,” Journal of Information Security and Applications, vol. 48, p. 102362, 2019.
  8. A. Atayero and O. Feyisetan, “Security issues in cloud computing: The potentials of homomorphic encryption,” Journal of Emerging Trends in Computing and Information Sciences, vol. 2, no. 10, pp. 546– 552, 2011.
  9. Archer, L. Chen, J. H. Cheon, R. Gilad-Bachrach, R. A. Hallman, Z. Huang, X. Jiang, R. Kumaresan, B. A. Malin, H. Sofia et al., “Applications of homomorphic encryption,” Homomorphic Encryption. org, Redmond WA, Tech. Rep., 2017. https://www.researchgate.net/publication/320976976_APPLICATIONS_OF_HOMOMORPHIC_ENCRYPTION
  10. Manish M Poteya, Dr C A Dhoteb, Mr Deepak H Sharmac, Homomorphic Encryption for Security of Cloud Data, Computing and Virtualization, 7th International Conference on Communication, Procedia Computer Science volume 79: 175-181 (2016).
  11. Aganya K, Sharma I. Symmetric Fully Homomorphic Encryption Scheme with Polynomials Operations. 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA). 2018:1954-1957. doi:10.1109/iceca.2018.8474729
  12. Biksham, V., and D. Vasumathi. “A lightweight fully homomorphic encryption scheme for cloud security,” International Journal of Information and Computer Security. 2020; 13(3-4): 357-371.
  13. Aubry P, Carpov S, Sirdey R. Faster Homomorphic Encryption is not Enough: Improved Heuristic for Multiplicative Depth Minimization of Boolean Circuits. Lecture Notes in Computer Science. 2020:345-363. doi:10.1007/978-3-030-40186-3_15
  14. Mittal, Sonam, and K. R. Ramkumar. “Research perspectives on fully homomorphic encryption models for cloud sector,” Journal of Computer Security 29, no. 2, pp.135-160, 2021.
  15. Savita A. Harkude DGNKR. Elliptic Curve Cryptography Based Homomorphic End-to-End Encryption Security in Cloud Computing. Mathematical Statistician and Engineering Applications. 2022;71(3s). doi:10.17762/msea.v71i3s.8
  16. Mahato GK, Chakraborty SK. A Comparative Review on Homomorphic Encryption for Cloud Security. IETE Journal of Research. 2021;69(8):5124-5133. doi:10.1080/03772063.2021.1965918
  17. Dasgupta S, Pal SK. Design of a polynomial ring based symmetric homomorphic encryption scheme. Perspectives in Science. 2016;8:692-695. doi:10.1016/j.pisc.2016.06.061
  18. Agrawal R, Joshi A. On Architecting Fully Homomorphic Encryption-based Computing Systems. Synthesis Lectures on Computer Architecture. 2023. doi:10.1007/978-3-031-31754-5
Support