A Cloud Based Dispersion and Encryption Based for Storage Mechanism

Authors

  • P. Munijyothika  Mother Theresa Institute of computer Applications , Palamaner- S. V University, Tirupati, India
  • Mr. A. Murali Mohan Kumar  Mother Theresa Institute of computer Applications , Palamaner- S. V University, Tirupati, India

Keywords:

Cloud computing, data dispersion, data encryption, key management, storage security.

Abstract

Cloud storage service has shown its great power and wide popularity which provides fundamental support for rapid development of cloud computing. However, due to management negligence and malicious attack, there still lie enormous security incidents that lead to quantities of sensitive data leakage at cloud storage layer. From the perspective of protecting cloud data confidentiality, this paper proposed a Cloud Secure Storage Mechanism named CSSM. To avoid data breach at the storage layer, CSSM integrated data dispersion and distributed storage to realize encrypted, chucked and distributed storage. In addition, CSSM adopted a hierarchical management approach and combined user password with secret sharing to prevent cryptographic materials leakage. The experimental results indicate that proposed mechanism is not only suitable for ensuring the data security at storage layer from leakage, but also can store huge amount of cloud data effectively without imposing too much time overhead. For example, when users upload/download 5G sized file with CSSM, it only takes 646seconds/269seconds, which is acceptable for users

References

  1. Bhardwaj, F. Al-Turjman, M. Kumar, T. Stephan, and L. Mostarda, ‘‘Capturing-the-invisible (CTI): Behavior-based attacks recognition in IoT-oriented industrial control systems,’’ IEEE Access, vol. 8, pp. 104956–104966, 2020.
  2. M. Kumar, A. Rani, and S. Srivastava, ‘‘Image forensics based on lighting estimation,’’ Int. J. Image Graph., vol. 19, no. 3, Jul. 2019, Art. no. 1950014.
  3. M. Kumar, S. Srivastava, and N. Uddin, ‘‘Image forensic based on lighting estimation,’’ Austral. J. Forensic Sci., vol. 51, no. 3, pp. 243–250, Aug. 2017.
  4. J. Li, Y. Zhang, X. Chen, and Y. Xiang, ‘‘Secure attribute-based data sharing for resource-limited users in cloud computing,’’ Comput. Secur., vol. 72, pp. 1–12, Jan. 2018.
  5. Y. Zhang, X. Chen, J. Li, D. S. Wong, H. Li, and I. You, ‘‘Ensuring attribute privacy protection and fast decryption for outsourced data security in mobile cloud computing,’’ Inf. Sci., vol. 379, pp. 42–61, Feb. 2017.
  6. The OpenStack Project. OSSA-2015-006: Unauthorized Delete of Versioned Swift Object. Accessed: Apr. 14, 2015. [Online]. Available: https://security.openstack.org/ossa/OSSA-2015-006.html
  7. The OpenStack Project. OSSA-2015-016: Information Leak Via Swift Tempurls. Accessed: Aug. 26, 2015. [Online]. Available: https://security. openstack.org/ossa/OSSA-2015-016.html
  8. The OpenStack Project. Possible Glance Image Exposure Via Swift. Accessed: Feb. 23, 2015. [Online]. Available: https://wiki. openstack.org/wiki/OSSN/OSSN-0025
  9. Cloud Security Alliance. Top Threats to Cloud Computing: Deep Dive. Accessed: Aug. 8, 2018. [Online]. Available: https://downloads. cloudsecurityalliance.org/assets/research/top-threats/top-threats-to-cloudcomputing-deep-dive.pdf
  10. The OpenStack Project. OpenStack Security Advisories. Accessed: Feb. 2, 2015. [Online]. Available: https://security.openstack.org/ossalist. html
  11. Common Vulnerabilities and Exposures. CVE-2015-5223. Accessed: Jul. 1, 2015. [Online]. Available: https://cve.mitre.org/cgi-bin/cvename. cgi?name=CVE-2015-5223
  12. Common Vulnerabilities and Exposures. CVE-2016-9590. Accessed: Nov. 23, 2016. [Online]. Available: https://cve.mitre.org/cgi-bin/cvename. cgi?name=CVE-2016-9590
  13. S. Y. Shah, B. Paulovicks, and P. Zerfos, ‘‘Data-at-rest security for spark,’’ in Proc. IEEE Int. Conf. Big Data (Big Data), Washington DC, USA, Dec. 2016, pp. 1464–1473.
  14. Z. Liu, Y. Huang, J. Li, X. Cheng, and C. Shen, ‘‘DivORAM: Towards a practical oblivious RAM with variable block size,’’ Inf. Sci., vol. 447, pp. 1–11, Jun. 2018.
  15. X. Zhang, X. Chen, J. Wang, Z. Zhan, and J. Li, ‘‘Verifiable privacypreserving single-layer perceptron training scheme in cloud computing,’’ Soft Comput., vol. 22, no. 23, pp. 7719–7732, Dec. 2018.

Downloads

Published

2022-10-22

Issue

Section

Research Articles

How to Cite

[1]
P. Munijyothika, Mr. A. Murali Mohan Kumar, " A Cloud Based Dispersion and Encryption Based for Storage Mechanism" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.251-260, September-October-2022.