Cloud storage services enable individuals and organizations to outsource data storage to remote servers. Cloud storage providers generally adopt data de-duplication, a technique for eliminating redundant data by keeping only a single copy of a file, thus saving a considerable amount of storage and bandwidth. However, an attacker can abuse de-duplication protocols to steal information. At present, there is a considerable increase in the amount of data stored in storage services, along with dramatic evolution of networking techniques. In storage services with huge data, the storage servers may want to reduce the volume of stored data, and the clients may want to monitor the integrity of their data with a low cost, since the cost of the functions related to data storage increase in proportion to the size of the data. To achieve these goals, secure de-duplication and integrity auditing delegation techniques have been studied, which can reduce the volume of data stored in storage by eliminating duplicated copies and permit clients to efficiently verify the integrity of stored files by delegating costly operations to a trusted party, respectively. This paper present study and development of a prototype for role and attribute based de-duplication.

Data de-duplication, data reduction, de-duplication approaches, role based, attribute based de-duplication

[1] F. Durao, J. F. S. Carvalho, A. Fonseka, and V. C. Garcia, “A systematic review on cloud computing,” The Journal of Supercomputing, vol. 68, no. 3, pp. 1321–1346, 2014.
[2] P. Mell and T. Grance, “The NIST definition of cloud computing,”
National Institute of Standards and Technology, Information Technology Laboratory, Tech. Rep., 2009.
[3] “Google Drive,” 2017. [Online]. Available: https://www.google.
com/drive/
[4] “DropBox, a file-storage and sharing service.” [Online]. Available:
http://www.dropbox.com
[5] “Mozy, cloud backup solutions.” [Online]. Available: https:
//www.mozy.com
[6] D. T. Meyer and W. J. Bolosky, “A study of practical deduplication,”, ACM Transactions on Storage, vol. 7, no. 4, pp. 1–20, 2012.
[7] N. Mandagere, P. Zhou, M. A. Smith, and S. Uttamchandani,
“Demystifying data deduplication,” in Proceedings of the
ACM/IFIP/USENIX Middleware ’08 Conference Companion (Companion’08), 2008, pp. 12–17.
[8] D. Harnik, B. Pinkas, and A. Shulman-Peleg, “Side Channels in
Cloud Services: Deduplication in Cloud Storage,” IEEE Security & Privacy Magazine, vol. 8, no. 6, pp. 40–47, 2010.
[9] Nagapramod Mandagere, Pin Zhou, Mark A Smith, and Sandeep Uttamchandani. “Demystifying data deduplication”. In Proceedings of the ACM/IFIP/USENIX Middleware’08 Conference Companion, pages 12–17. ACM,2008.
[10] Mark W Storer, Kevin Greenan, Darrell DE Long, and Ethan L Miller. “Secure data deduplication”. In Proceedings of the 4th ACM international workshop on Storage security and survivability,pages 1–10. ACM, 2008.
[11]Ravindra Mahabaleshwar. “Effective data deduplication implementation”, Whitepaper 2011.
[12]Qinlu He, Zhanhuai Li, Xiao Zhang, “Data De-duplication Techniques”, International Conference on Future Information Technology and Management Engineering, IEEE 2010
[13] Dave Cannon. Data deduplication and tivoli storage manager. Tivoli Storage, IBM Software Group (September 2007), 2009
[14] AndrejTolic, AndrejBrodnik, “Deduplication in unstructured-data storae systems”, ELEKTROTEHNISKI VESTNIK 82(5): 233–242, 2015
[15]E. Manogar, S. Abirami, “A Study on Data Deduplication Techniques for Optimized Storage”, 2014 Sixth International Conference on Advanced Computing(lCoAC) IEEE
[16] Vruti Satish Radia, Dheeraj Kumar Singh, “ Secure deduplication Techniques: A Study”, International Journal of Computer Applications (0975 – 8887) Volume 137 – No.8, March 2016