Skip to main content
SpringerLink
Log in

Guaging the Effectivity of Existing Security Measures for Big Data in Cloud Environment

  • Conference paper
  • First Online:
Book cover Software Engineering Trends and Techniques in Intelligent Systems (CSOC 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 575))

Included in the following conference series:

Abstract

As the technology is improving, today’s era is focusing towards big data. In that sense, various organizations are demanding an efficient data storage mechanism and also the efficient data analysis. The Big Data (BD) also faces some of the security issues for the important data or information which is shared or transferred over the cloud. These issues include the tampering, losing control over the data, etc. This survey work offers some of the interesting, important aspects of big data including the high security and privacy issue. In this, the survey of existing research works for the preservation of privacy and security mechanism and also the existing tools for it are stated. The discussions for upcoming tools which are needed to be focused on performance improvement are discussed. With the survey analysis, a research gap is illustrated, and a future research idea is presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lohr, S.: The age of Big Data, vol. 11. New York Times (2012)

    Google Scholar 

  2. Swan, M.: The quantified self: fundamental disruption in big data science and biological discovery. Big Data 1(2), 85–99 (2013)

    Article  Google Scholar 

  3. Provost, F., Fawcett, T.: Data science and its relationship to big data and data-driven decision making. Big Data 1(1), 51–59 (2013)

    Article  Google Scholar 

  4. Analytics, Big Data. Big data analytics for security (2013)

    Google Scholar 

  5. Wang, C.: Privacy-preserving public auditing for data storage security in cloud computing. In: Infocom, 2010 Proceedings IEEE (2010)

    Google Scholar 

  6. Tene, O., Polonetsky, J.: Big data for all: Privacy and user control in the age of analytics. Nw. J. Tech. Intell. Prop 11, xxvii (2012)

    Google Scholar 

  7. Villars, R.L., Olofson, C.W., Eastwood, M.: Big Data: What It Is and Why You Should Care. White Paper, IDC, Framingham (2011)

    Google Scholar 

  8. Kitchenham, B., et al.: Systematic literature reviews in software engineering–a systematic literature review. Inf. Softw. Technol. 51(1), 7–15 (2009)

    Article  Google Scholar 

  9. Rubinstein, I.: Big data: the end of privacy or a new beginning? In: International Data Privacy Law (Forthcoming), pp. 12–56 (2013)

    Google Scholar 

  10. James, B.D.: Security and privacy challenges in cloud computing environments. 8, 24–31 (2010)

    Google Scholar 

  11. Katal, A., Wazid, M., Goudar, R.H.: Big data: issues, challenges, tools and good practices. In: Sixth International Conference on Contemporary Computing (IC3). IEEE (2013)

    Google Scholar 

  12. Sweeney, L.: K-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(05), 557–570 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  13. Hashem, I., Targio, A.: The rise of “big data” on cloud computing: review and open research issues. Inf. Syst. 47, 98–115 (2015)

    Article  Google Scholar 

  14. 5 Hadoop Security Projects. https://www.xplenty.com/blog/2014/11/5-hadoop-security-projects/

  15. Lei, X., Jiang, C., Wang, J., Yuan, J., Ren, Y.: Information security in big data: privacy and data mining. IEEE Access 2, 1149–1176 (2014)

    Article  Google Scholar 

  16. Hu, J., Vasilakos, A.V.: Energy big data analytics and security: challenges and opportunities. IEEE Trans. Smart Grid 7(5), 2423–2436 (2016)

    Article  Google Scholar 

  17. Yan, Z., Ding, W., Yu, X., Zhu, H., Deng, R.H.: Deduplication on encrypted big data in cloud. IEEE Trans. Big Data 2(2), 138–150 (2016)

    Article  Google Scholar 

  18. Xu, L., Jiang, C., Chen, Y., Wang, J., Ren, Y.: A framework for categorizing and applying privacy-preservation techniques in big data mining. Computer 49(2), 54–62 (2016)

    Article  Google Scholar 

  19. Liang, K., Susilo, W., Liu, J.K.: Privacy-preserving ciphertext multi-sharing control for big data storage. IEEE Trans. Inf. Forensics Secur. 10(8), 1578–1589 (2015)

    Article  Google Scholar 

  20. Perera, C., Ranjan, R., Wang, L., Khan, S.U., Zomaya, A.Y.: Big data privacy in the internet of things era. IT Professional 17(3), 32–39 (2015)

    Article  Google Scholar 

  21. Nedelcu, B.: About big data and its challenges and benefits in manufacturing. Database Syst. J. 4(3), 10–19 (2013)

    Google Scholar 

  22. Gaff, B.M., Sussman, H.E., Geetter, J.: Privacy and big data. Computer 47(6), 7–9 (2014)

    Article  Google Scholar 

  23. Cárdenas, A.A., Manadhata, P.K., Rajan, S.P.: Big data analytics for security. IEEE Secur. Priv. 11(6), 74–76 (2013)

    Article  Google Scholar 

  24. Yu, S., Liu, M., Dou, W., Liu, X., Zhou, S.: Networking for big data: a survey. IEEE Commun. Surv. Tutorials PP(99), 1 (2016)

    Google Scholar 

  25. Baek, J., Vu, Q.H., Liu, J.K., Huang, X., Xiang, Y.: A secure cloud computing based framework for big data information management of smart grid. IEEE Trans. Cloud Comput. 3(2), 233–244 (2015)

    Article  Google Scholar 

  26. Dong, X., Li, R., He, H., Zhou, W., Xue, Z., Wu, H.: Secure sensitive data sharing on a big data platform. Tsinghua Sci. Technol. 20(1), 72–80 (2015)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of CSE, RNS Institute of Technology, Bangalore, India

    Chhaya S. Dule & H. A. Girijamma

  2. Jyothy Institute of Technology, Bangalore, India

    Chhaya S. Dule

  3. Department of CSE, Visvesvaraya Technological University (VTU), Belgaum, Karnataka, India

    Chhaya S. Dule & H. A. Girijamma

Authors
  1. Chhaya S. Dule
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. A. Girijamma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chhaya S. Dule .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Petr Silhavy

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zdenka Prokopova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Roman Senkerik

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlin, Czech Republic

    Zuzana Kominkova Oplatkova

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Dule, C.S., Girijamma, H.A. (2017). Guaging the Effectivity of Existing Security Measures for Big Data in Cloud Environment. In: Silhavy, R., Silhavy, P., Prokopova, Z., Senkerik, R., Kominkova Oplatkova, Z. (eds) Software Engineering Trends and Techniques in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 575. Springer, Cham. https://doi.org/10.1007/978-3-319-57141-6_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-57141-6_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57140-9

  • Online ISBN: 978-3-319-57141-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation