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Improve Speed Efficiency and Maintain Data Integrity of Dynamic Big Data by using Map Reduce

by Sapna R. Kadam, B.M. Patil, V.M. Chandode
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 137 - Number 8
Year of Publication: 2016
Authors: Sapna R. Kadam, B.M. Patil, V.M. Chandode
10.5120/ijca2016908687

Sapna R. Kadam, B.M. Patil, V.M. Chandode . Improve Speed Efficiency and Maintain Data Integrity of Dynamic Big Data by using Map Reduce. International Journal of Computer Applications. 137, 8 ( March 2016), 5-12. DOI=10.5120/ijca2016908687

@article{ 10.5120/ijca2016908687,
author = { Sapna R. Kadam, B.M. Patil, V.M. Chandode },
title = { Improve Speed Efficiency and Maintain Data Integrity of Dynamic Big Data by using Map Reduce },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 137 },
number = { 8 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 5-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume137/number8/24293-2016908687/ },
doi = { 10.5120/ijca2016908687 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:37:48.291916+05:30
%A Sapna R. Kadam
%A B.M. Patil
%A V.M. Chandode
%T Improve Speed Efficiency and Maintain Data Integrity of Dynamic Big Data by using Map Reduce
%J International Journal of Computer Applications
%@ 0975-8887
%V 137
%N 8
%P 5-12
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing has rapid growth globally cause of the facet provided by the service not only scalability but also capacity management that subject to storage huge amount of data. Major issue will going to arrived at the time of storing this much bulky data on a cloud because data integrity may lost at the time of data retrieval.First, Anyone canister to challenge in the intention to verification of data integrity of certain file so that appropriate authentication process will going to miss between cloud service provider and third party auditor(TPA). Second, as the BLS signature obligated for fully dynamic updates of data over data blocks of fixed sized which causes re-computation and updating for an entire block of authenticator which origin not only higher storage but also communication overheads. In order to keep security as a vital issue because malicious party may scarf data at the time of data flows this can be addressed by means of symmetric key encryption. Similarly, in order to increase the speed and efficiency at the time of data retrieval for huge amount of data MapReduce plays vital role and the because of replication over the HDFS maintain data integrity with the full support of dynamic updates.

References
  1. R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, ‘‘Cloud Computing and Emerging IT Platforms: Vision, Hype, Reality for Delivering Computing as the 5th Utility,’’ Future Gen. Comput. Syst., vol. 25, no. 6, pp. 599-616, June 2009.
  2. M.Armbrust, A. Fox, R. Griffith, A.D. Joseph, R.Katz, A.Konwinski,G. Lee, D. Patterson, A. Rabkin, I. Stoica, andM. Zaharia, ‘‘AView of Cloud Computing,’’ Commun. ACM, vol. 53, no. 4, pp. 50-58, Apr. 2010.
  3. Customer Presentations on Amazon Summit Australia, Sydney, 2012, accessed on: March 25, 2013.
  4. J. Yao, S. Chen, S.Nepal,D. Levy, and J. Zic, ‘‘TrustStore: Making Amazon S3 Trustworthy With Services Composition,’’ in Proc. 10th IEEE/ACM Int’l Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2010, pp. 600-605.
  5. D. Zissis and D. Lekkas, ‘‘Addressing Cloud Computing Security Issues,’’ Future Gen. Comput. Syst., vol. 28, no. 3, pp. 583-592, Mar. 2011.
  6. Q. Wang, C.Wang, K. Ren,W. Lou, and J. Li, ‘‘Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing,’’ IEEE Trans. Parallel Distrib. Syst., vol. 22, no. 5, pp. 847-859, May 2011.
  7. C. Wang, Q. Wang, K. Ren, and W. Lou, ‘‘Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing,’’ in Proc. 30st IEEE Conf. on Comput. and Commun. (INFOCOM), 2010, pp. 1-9.
  8. A. Juels and B.S. Kaliski Jr., ‘‘PORs: Proofs of Retrievability for Large Files,’’ in Proc. 14th ACM Conf. on Comput. and Commun. Security (CCS), 2007, pp. 584-597
  9. G. Ateniese, R.D. Pietro, L.V. Mancini, and G. Tsudik, ‘‘Scalable and Efficient Provable Data Possession,’’ in Proc. 4th Int’l Conf. Security and Privacy in Commun. Netw. (SecureComm), 2008, pp. 1-10.
  10. G. Ateniese, R. Burns, R. Curtmola, J. Herring, O. Khan, L. Kissner, Z. Peterson, and D. Song, ‘‘Remote Data Checking Using Provable Data Possession,’’ ACM Trans. Inf. Syst. Security, vol. 14, no. 1, May 2011, Article 12.
  11. G.Ateniese, R.B. Johns,R. Curtmola, J.Herring, L. Kissner,Z. Peterson, and D. Song, ‘‘Provable Data Possession at Untrusted Stores,’’ in Proc. 14th ACM Conf. on Comput. and Commun. Security (CCS), 2007, pp. 598-609.
  12. R. Curtmola, O. Khan, R.C. Burns, and G. Ateniese, ‘‘MR-PDP: Multiple-Replica Provable Data Possession,’’ in Proc. 28th IEEE Conf. on Distrib. Comput. Syst. (ICDCS), 2008, pp. 411-420.
  13. C. Erway, A. Ku¨ pc¸u¨ , C. Papamanthou, and R. Tamassia, ‘‘Dynamic Provable Data Possession,’’ in Proc. 16th ACM Conf. on Compute. and Commun. Security (CCS), 2009, pp. 213-222.
  14. G. Ateniese, S. Kamara, and J. Katz, ‘‘Proofs of Storage From Homomorphic Identification Protocols,’’ in Proc. 15th Int’l Conf. on Theory and Appl. of Cryptol. and Inf. Security (ASIACRYPT), 2009, pp. 319-333.
  15. Y. Zhu, H. Hu, G.-J. Ahn, and M. Yu, ‘‘Cooperative Provable Data Possession for Integrity Verification in Multi-Cloud Storage,’’ IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 12, pp. 2231-2244, Dec. 2012.
  16. H. Shacham and B. Waters, ‘‘Compact Proofs of Retrievability,’’ in Proc. 14th Int’l Conf. on Theory and Appl. of Cryptol. and Inf. Security (ASIACRYPT), 2008, pp. 90-107.
  17. S. Nepal, S. Chen, J. Yao, and D. Thilakanathan, ‘‘DIaaS: Data Integrity as a Service in the Cloud,’’ in Proc. 4th Int’l Conf. on Cloud Computing (IEEE CLOUD), 2011, pp. 308-315.
  18. E. Naone, ‘‘What Twitter Learns From All Those Tweets,’’ in Technology Review, Sept. 2010, accessed on: March 25, 2013. [Online]. Available: http://www.technologyreview.com/view/420968/what-twitter-learns-from-all-those-tweets/
  19. Y. He, S. Barman, and J.F. Naughton, ‘‘Preventing Equivalence Attacks in Updated, Anonymized Data,’’ in Proc. 27th IEEE Int’l Conf. on Data Engineering (ICDE), 2011, pp. 529-540.
  20. X. Zhang, L.T. Yang, C. Liu, and J. Chen, ‘‘A Scalable Two-Phase Top-Down Specialization Approach for Data Anonymization Using MapReduce on Cloud,’’ IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 2, pp. 363-373, Feb. 2014.
  21. S.E. Schmidt, ‘‘Security and Privacy in the AWS Cloud,’’ presented at the Presentation Amazon Summit Australia, Sydney,Australia,May 2012, accessed on: March 25, 2013. [Online]. Available: http://aws.amazon.com/apac/awssummit-au/.
  22. C. Liu, X. Zhang, C. Yang, and J. Chen, ‘‘CCBKEVSession Key Negotiation for Fast and Secure Scheduling of Scientific Applications in Cloud Computing,’’ Future Gen. Comput. Syst.,vol. 29, no. 5, pp. 1300-1308, July 2013.
  23. C. Liu, N. Beaugeard, C. Yang, X. Zhang and J. Chen, “HKE-BC: HierarchicalKey Exchange for Secure Scheduling and Auditing of Big Data in Cloud Computing, Concurrency and Computation” Practice and Experience, accepted on 3 October, 2014.
  24. C., Chen, J., Yang, L. T., Zhang, X., Yang, C., Ranjan, R. & Ramamohanarao, K. 2014b “Authorized Public Auditing of Dynamic Big Data Storage on Cloud with Efficient Verifiable Fine-grained Updates” IEEE Transactions on Parallel and Distributed Systems, 25, 2234 -244.
  25. KVM Hypervisor, accessed on: March 25, 2013. [Online]. Available: www.linux-kvm.org/.
  26. Hadoop MapReduce. [Online]. Available: http://hadoop.apache.org
  27. OpenStack Open Source Cloud Software, accessed on: March 25, 2013. [Online]. Available: http://openstack.org/
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing authorized auditing big data Hadoop provable data possession fine-grained updates

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