STLDAS: Secure Two Level Deduplication and Auditing of Shared Data in Cloud

C. M. Geeta, G. Mithila Lakshmi, R. G. Shreyas Raju, S. Raghavendra, Rajkumar Buyya, K. R. Venugopal, S. S. Iyengar, L. M. Patnaik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the cloud repository service furnished by the cloud computing, users can comfortably arrange themselves as a cluster and distribute information effectively. In order to empower public verifier to audit the distributed information, clients in the cluster need to Figure out signatures on complete chunks of collaborative information. Every client in the cluster modifies and signs his respective chunks, and deploys in the cloud server. Hence specific chunks of shared information are normally signed by specific clients. If anyone of the customers' is found malicious, he is immediately repudiated from the cluster. The prevailing clients in the cluster are permitted to re-sign the chunks that were earlier signed by this eliminated client. This approach is inefficient due to the massive amount of collaborative information in the cloud. By exploiting the approach of proxy re-signatures, the CSP is acknowledged to re-sign chunks in support of the prevailing clients during customer repudiation. When many clients deploy the same information to the cloud repository, repository space has identical copies, hence deduplication technology is usually utilized to lower the capacity and bandwidth prerequisites of the utilities by removing repetitious information and hoarding only an original replica of them. In order to assimilate both data honesty and deduplication in cloud, we present a novel Secure Two Level Deduplication and Auditing of Shared Data in Cloud (STLDAS) mechanism. Experimental results show that our mechanism achieves secure deduplication and appreciable improvement in tag generation.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE Region 10 Symposium, TENSYMP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages698-703
Number of pages6
ISBN (Electronic)9781728102979
DOIs
Publication statusPublished - 06-2019
Event2019 IEEE Region 10 Symposium, TENSYMP 2019 - Kolkata, India
Duration: 07-06-201909-06-2019

Publication series

NameProceedings of 2019 IEEE Region 10 Symposium, TENSYMP 2019

Conference

Conference2019 IEEE Region 10 Symposium, TENSYMP 2019
Country/TerritoryIndia
CityKolkata
Period07-06-1909-06-19

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Control and Optimization
  • Health Informatics

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