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Group Data Verification for Enhancing the Storage Security in Cloud Computing


  • Faculty of Computing, Sathyabama University, Chennai - 600119, Tamil Nadu, India


Objectives: A privacy-preserving mechanism for public auditing of shared data in cloud storage has been proposed. This boosts up the effectiveness of the verification task which is meant for auditing multiple tasks. It also reduces the response time and auditing time and thereby improves data integrity. Methods/Analysis: A privacy preserving methodology has been proposed which sustains the social interaction and examination on the data which is being mutually shared across the cloud. In scrupulous, ring signatures have been utilized to enhance the verifiability of the computed metadata and to improve the accuracy of the group data analysis. The proposed system maintains the secrecy of the mutual data. The confidentiality of the specific user in the group is ensured by data filtering mechanism. This mechanism masks the user’s private data from being accessed publicly across the cloud. The proposed system also supports multi-group audits simultaneously. Findings: A distinct privacy preserving mechanism is rarely available in the cloud storage especially for shared data. Also the personal information should not be disturbed by public verifiers. The ring mechanism shares only the verified information instead of sharing the entire file. This improves the integrity of the confidential data. The mechanism boosts the potency of substantive multi-group analysis to support the entire data cluster. This improvises the real time cloud data distribution. The identity of the signer is traceable by the group owner. Novelty/Improvement: Only registered users can login to the cloud. This prevents the unauthorized access to the cloud. Data is secured during cloud upload. Other users in the group have no permission to modify the data. Except the signer other users have got read-only permission.


Auditing, Authenticators, Batch Auditing, Potency, Privacy, Shared Information.

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  • Wang B, Li B, Li H. Oruta: Privacy- preserving public auditing for shared data in the cloud. IEEE Transactions on Cloud Computing. 2014 Apr; 2(1):46–53.
  • Armbrust M, Fox A, Griffith R, Joseph AD, Katz RH, Konwinski A, Lee G, Patterson DA, Rabkin A, Stoica I, Zaharia M. A view of cloud computing, communications of the ACM. 2010 Apr; 53(4):50–8.
  • Ren K, Wang C, Wang Q. Security challenges for the public cloud. IEEE Internet Computing. 2012 Jan; 16(1):69–73.
  • Song D, Shi E, Fischer I, Shankar U. Cloud data protection for the masses. Computer. 2012 Jan; 45(1):39–45.
  • Wang C, Wang Q, Ren K, Lou W. Privacy-preserving public auditing for data storage security in cloud computing. Proceedings of the IEEE INFOCOM; San Diego. 2010 Mar. p. 1–9.
  • Vigneshwari S, Aramudhan M. Web information extraction on multiple ontologies based on concept relationships upon training the user profiles. Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. 2014 Nov; 1–8.
  • Wang B, Li M, Chow SS, Li H. Computing encrypted cloud data efficiently under multiple keys. 2013 IEEE Conference on Communications And Network Security (CNS); 2013 Oct. p. 504–13.
  • Rivest R, Shamir A, Adleman L. A method for obtaining digital signatures and public key cryptosystems. Communications of the ACM. 1978 Feb; 21(2):120–6.
  • Vigneshwari S, Aramudhan M. Personalized cross ontological framework for secured document retrieval in the cloud. National Academy Sciences Letters-India. 2015; 38(5):421–4.
  • Saranya R, Gowri S, Monisha S, Vigneshwari S. An ontological approach for originating data services with hazy semantics. Indian Journal of Science and Technology. 2016 Jun; 9(23). DOI: 10.17485/ijst/2016/v9i23/95145.
  • Kalpana S, Vigneshwari S. Selecting multiview point similarity from different methods of similarity measure to perform document comparison. Indian Journal of Science and Technology. 2016 Mar; 9(10). DOI: 10.17485/ijst/2016/ v9i10/88903.
  • Vigneshwari S, Aramudhan M. Social information retrieval based on semantic annotation and hashing upon the multiple ontologies. Indian Journal of Science and Technology.2015 Jan; 8(2):103–7.


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