Advertisement

A fully homomorphic–elliptic curve cryptography based encryption algorithm for ensuring the privacy preservation of the cloud data

  • G. Prabu Kanna
  • V. Vasudevan
Article
  • 251 Downloads

Abstract

Enabling a security and privacy preservation for the cloud data is one of the demanding and crucial tasks in recent days. Because, the privacy of the sensitive data should be safeguard from the unauthorized access for improving its security. So, various key generation, encryption and decryption mechanisms are developed in the traditional works for privacy preservation in cloud. Still, it remains with the issues such as increased computational complexity, time consumption, and reduced security. Also, the traditional works use the symmetric key cryptography based. Thus, this paper aims to develop a new privacy preservation mechanism by implementing a fully homomorphic–elliptic curve cryptography (FH-ECC) algorithm. The data owner encrypts the original data by converting it into the cipher format with the use of ECC algorithm, and applies the FH operations on the encrypted data before storing it on the cloud. When the user gives the data request to the cloud, the Cloud Service Provider verifies the access control policy of the user for enabling the restricted access on the data. If the access policy is verified, the encrypted data is provided to the user, from that the cipher text is extracted. Then, the ECC decryption and FH operations are applied to generate the original text. Based on the several analysis, the research work is evaluated with the help of different performance measures such as execution time, encryption time, and decryption time. In addition the effectiveness of the novel FHE technique is justified by the comparative analysis made with the traditional techniques.

Keywords

Security Privacy preservation Fully homomorphic encryption (FHE) Decryption Key generation Access policy verification 

References

  1. 1.
    Zhang, X., et al.: Privacy preservation over big data in cloud systems. In: Security, Privacy and Trust in Cloud Systems, Springer, pp. 239–257 (2014)Google Scholar
  2. 2.
    Prasad, P., et al.: Data sharing security and privacy preservation in cloud computing. In: Green Computing and Internet of Things (ICGCIoT), 2015 International Conference on, pp. 1070–1075 (2015)Google Scholar
  3. 3.
    Zhang, X., et al.: Scalable local-recoding anonymization using locality sensitive hashing for big data privacy preservation. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, pp. 1793–1802 (2016)Google Scholar
  4. 4.
    Suganthi, J., et al.: Privacy preservation and public auditing for cloud data using ASS in multi-cloud. In: Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on, pp. 1–6 (2015)Google Scholar
  5. 5.
    Wang, W., et al.: Outsourcing high-dimensional healthcare data to cloud with personalized privacy preservation. Comput. Netw. 88, 136–148 (2015)CrossRefGoogle Scholar
  6. 6.
    Li, F., et al.: Exploring privacy preservation in outsourced k-nearest neighbors with multiple data owners. In: Proceedings of the 2015 ACM Workshop on Cloud Computing Security Workshop, pp. 53–64 (2015)Google Scholar
  7. 7.
    He, X.-M., et al.: Semi-homogenous generalization: improving homogenous generalization for privacy preservation in cloud computing. J. Comput. Sci. Technol. 31, 1124–1135 (2016)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Liu, H., et al.: Shared authority based privacy-preserving authentication protocol in cloud computing. IEEE Trans. Parallel Distrib. Syst. 26, 241–251 (2015)CrossRefGoogle Scholar
  9. 9.
    Shen, Q., et al.: Exploiting geo-distributed clouds for a e-health monitoring system with minimum service delay and privacy preservation. IEEE J. Biomed. Health Inform. 18, 430–439 (2014)CrossRefGoogle Scholar
  10. 10.
    Wang, X.A., et al.: Efficient privacy preserving predicate encryption with fine-grained searchable capability for Cloud storage. Comput. Electr. Eng. 56, 871–883 (2016)CrossRefGoogle Scholar
  11. 11.
    Cao, N., et al.: Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 25, 222–233 (2014)CrossRefGoogle Scholar
  12. 12.
    Hayward, R., Chiang, C.-C.: Parallelizing fully homomorphic encryption for a cloud environment. J. Appl. Res. Technol. 13, 245–252 (2015)CrossRefGoogle Scholar
  13. 13.
    Dhote, C.: Homomorphic encryption for security of cloud data. Procedia Comput. Sci. 79, 175–181 (2016)CrossRefGoogle Scholar
  14. 14.
    El Makkaoui, K., et al.: Fast cloud-RSA scheme for promoting data confidentiality in the cloud computing. Procedia Comput. Sci. 113, 33–40 (2017)CrossRefGoogle Scholar
  15. 15.
    Dasgupta, S., Pal, S.: Design of a polynomial ring based symmetric homomorphic encryption scheme. Perspect. Sci. 8, 692–695 (2016)CrossRefGoogle Scholar
  16. 16.
    Farokhi, F., et al.: Secure and private cloud-based control using semi-homomorphic encryption. IFAC-PapersOnLine 49, 163–168 (2016)CrossRefGoogle Scholar
  17. 17.
    Kaaniche, N., Laurent, M.: Data security and privacy preservation in cloud storage environments based on cryptographic mechanisms. Comput. Commun. 111, 120–141 (2017)CrossRefGoogle Scholar
  18. 18.
    Yu, Y., et al.: Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Trans. Inf. Forensics Secur. 12, 767–778 (2017)CrossRefGoogle Scholar
  19. 19.
    Tang, J., et al.: Ensuring security and privacy preservation for cloud data services. ACM Comput. Surv. (CSUR) 49, 13 (2016)Google Scholar
  20. 20.
    Zhang, X., et al.: Proximity-aware local-recoding anonymization with mapreduce for scalable big data privacy preservation in cloud. IEEE Trans. Comput. 64, 2293–2307 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Xia, Z., et al.: A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 27, 340–352 (2016)CrossRefGoogle Scholar
  22. 22.
    Wang, B., et al.: Privacy-preserving multi-keyword fuzzy search over encrypted data in the cloud. In: INFOCOM, 2014 Proceedings IEEE, pp. 2112–2120 (2014)Google Scholar
  23. 23.
    Hariss, K., et al.: Fully enhanced homomorphic encryption algorithm of MORE approach for real world applications. J. Inf. Secur. Appl. 34, 233–242 (2017)Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Information TechnologyKalasalingam Academy of Research and EducationKrishnankoilIndia

Personalised recommendations