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Reseach Article

Functional Encryption for Secured Big Data Analytics

by Nilotpal Chakraborty, G K Patra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 16
Year of Publication: 2014
Authors: Nilotpal Chakraborty, G K Patra
10.5120/18836-0359

Nilotpal Chakraborty, G K Patra . Functional Encryption for Secured Big Data Analytics. International Journal of Computer Applications. 107, 16 ( December 2014), 19-22. DOI=10.5120/18836-0359

@article{ 10.5120/18836-0359,
author = { Nilotpal Chakraborty, G K Patra },
title = { Functional Encryption for Secured Big Data Analytics },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 16 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number16/18836-0359/ },
doi = { 10.5120/18836-0359 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:41:14.115833+05:30
%A Nilotpal Chakraborty
%A G K Patra
%T Functional Encryption for Secured Big Data Analytics
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 16
%P 19-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big Data has gained a lot of interest now a days due to the enormous scope it introduces for a better understanding of the business and decision making process for an organization. There has been a wide range of researches going on around the globe on this to make the most out of it and quite a number of technical platforms are available to perform various big data analytics. Though, Scientists and organizations have been able to develop systems that can handle the big data and perform analysis on it, the security aspects remains vastly untouched. As big data is ultimately some data that are to be stored and processed in digital format, all the data security problems are applicable to it also. In this paper, possible implementation of 'Functional encryption' has been proposed towards a secured big data analytics infrastructure.

References
  1. Discussion on Big data by Roger Magoulas, http://strata. oreilly. com/2010/01/roger-magoulas-on-big-data. html
  2. Gartner, Big Data Definition, http://www. gartner. com/it-glossary/big-data/, accessed in September, 2013
  3. A comprehensive list of Big Data Statistics, http://www. wikibon. rg/blog/big-data-statistics/
  4. Apache Hadoop homepage, http://www. hadoop. apache. org, accessed in September, 2013.
  5. The White Book of Big Data: The definitive guide to the revolution of business analytics, Fujitsu Services Ltd. , July 2013
  6. http://www. slashgear. com , accessed in August 2013
  7. Amit Sahai, Brent Waters, Fuzzy Identity-Based Encryption, Proceedings of Eurocrypt 2005.
  8. Dan Boneh, Amit Sahai, Brent Waters, Functional Encryption: Definitions and Challenges, Proceedings of Cryptography Conference, 2011.
  9. Craig Gentry. A fully homomorphic encryption scheme. PhD thesis, Stanford University, 2009. http://crypto. stanford. edu/craig
  10. Vipul Goyal, Omkant Pandey,Amit Sahai, Brent Waters, Attribute Based-Encryption for Fine-Grained Access Control of Encrypted Data, ACM CCS, 2006.
  11. S. Agarwal, S Gorbunov, V. Vaikuntanathan, H. Wee; Functional Encryption: New Perspective and Lower Bounds, Cryptology ePrint Archive, Report 2012/468, Available online: www. eprint. iacr. org/2012/468
  12. S. Agarwal, S. Agarwal, S. Badrinarayanan, A. Kumarasubramanian, M. Prabhakaran, A. Sahai; Function Private Functional Encryption and Property Preserving Encryption: New Definitions and Positive Results,Cryptology ePrint Archive, Report 2013/744, Available online: www. eprint. iacr. org/2013/744
  13. Marten van Dijk, Craig Gentry, Shai Halevi, and Vinod Vaikuntanathan. Fully homomorphic encryption over the integers. In Advances in Cryptology - EUROCRYPT'10, volume 6110 of Lecture Notes in Computer Science, pages 24-43. Springer, 2010. Full version available on-line from http://eprint. iacr. org/2009/616
  14. S Goldwasser, Y Kalai, R Popa, V Vaikuntanathan, N Zeldovich; Reusable Garbled Circuits and Succinct Functional Encryption, Cryptology ePrint Archive, Report 2012/733, Available online: https://eprint. iacr. org/2012/733
  15. C. Gentry. Fully homomorphic encryption using ideal lattices. In STOC '09, pages 169-178, ACM, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Big data fully homomorphic encryption functional encryption cryptography.