CFP last date
22 April 2024
Reseach Article

Analysis of Big Data Security Schemes for Detection and Prevention from Intruder Attacks in Cloud Computing

by Amit Chaturvedi, Fayaz Ahmad Lone
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 5
Year of Publication: 2017
Authors: Amit Chaturvedi, Fayaz Ahmad Lone
10.5120/ijca2017912831

Amit Chaturvedi, Fayaz Ahmad Lone . Analysis of Big Data Security Schemes for Detection and Prevention from Intruder Attacks in Cloud Computing. International Journal of Computer Applications. 158, 5 ( Jan 2017), 26-30. DOI=10.5120/ijca2017912831

@article{ 10.5120/ijca2017912831,
author = { Amit Chaturvedi, Fayaz Ahmad Lone },
title = { Analysis of Big Data Security Schemes for Detection and Prevention from Intruder Attacks in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 5 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number5/26905-2017912831/ },
doi = { 10.5120/ijca2017912831 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:02.215721+05:30
%A Amit Chaturvedi
%A Fayaz Ahmad Lone
%T Analysis of Big Data Security Schemes for Detection and Prevention from Intruder Attacks in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 5
%P 26-30
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big Data Security is a major paradigm for research on cloud networks. Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted substantial interest from both academics and practitioners. Big Data Analytics (BDA) is increasingly becoming a trending practice that many organizations are adopting with the purpose of constructing valuable information from BD. The analytics process, including the deployment and use of BDA tools, is seen by organizations as a tool to improve operational efficiency though it has strategic potential, drive new revenue streams and gain competitive advantages over business rivals. In this paper, our aim to present the various application of IDS in cloud computing.

References
  1. Zhiyuan Tan, Upasana T. Nagar, Xiangjian He, and Priyadarsi Nanda, Ren Ping Liu, Song Wang, Jiankun Hu, “Enhancing Big Data Security with Collaborative Intrusion Detection”, IEEE Cloud Computing published by the IEEE computer society, 2325-6095, pp. 34-40.
  2. Victor, N., Lopez, D., & Abawajy, J. H.. Privacy models for big data: a survey. International Journal of Big Data Intelligence, 2016 3(1), 61-75.
  3. Lopez, D., & Gunasekaran, M. Assessment of Vaccination Strategies Using Fuzzy Multi-criteria Decision Making. In Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015) 2015: 195-208. Springer
  4. Lopez, D., Gunasekaran, M., Murugan, B. S., Kaur, H., & Abbas, K. M. Spatial big data analytics of influenza epidemic in Vellore, India. In 2014 IEEE International Conference on Big Data (Big Data), 2014, October: 19-24. IEEE.
  5. Thilagavathi, M., Lopez, D., & Murugan, B. S. Middleware for Preserving Privacy in Big Data. Handbook of Research on Cloud Infrastructures for Big Data Analytics, IGI Global, 2014.
  6. David Gill and II-Yeol Song, “Modeling and Management of Big Data: Challenges and opportunities”, Future Generation Computer Systems 63(2016), pp 96-99
  7. M.M. Potel, C A Dhote, D.H. Sharma, “Homomorphic Encryption for Security of Cloud Data”, Procedia Computer Science 79 (2016), pp. 175-181.
  8. Zhong Wang, Qian Yu, “Privacy trust crisis of personal data in China in the era of Big Data: The survey and countermeasures”, Computer Law & Security Review 31(2015), pp.782-792
  9. N. Kshetri, “Big data’s impact on privacy, security and customer welfare”, Telecommunicaitons Policy 38 (2014), pp.1134-1145.
  10. S.Akter, S.F.Wamba, A.Gunasekaran, R. Dubey, S. J.Childe, “How to improve firm performance using big data analytics capability and business strategy alignment?”, International Journal of Production Economics, 182 (2016), pp.113-131.
  11. A. Siddiqa, I.A.T. Hashem, I.Yaqoob, M.Marjani, S. Shamshirband, A. Gani, F.Nasaruddin, “A Survey of big data management: Taxonomy and state-of-the-art”, 71 (2016), pp. 151-166.
  12. R. Shaikh, M. Sasikumar, “Trust Model for Measuring Security Strength of Cloud Computing Service”, Procedia Computer Science 45 (2015), pp 380-389
  13. Vennila.S, and Priyandarshini J. , “Scalable Privacy Preservation in Big Data A Survey”, Procedia Computer Science 50 (2015), pp. 369-373
  14. B. H. Krishnaa, Dr. S. Kiranb, G. Muralia, R.P.K. Reddy, “Security Issues In Service Model Of Cloud Computing Environment”, Procedia Computer Science 87 (2016),pp 246-251
  15. N. Khana, A. Al-Yasirib, “Identifying Cloud Security Threats to Strengthen Cloud Computing Adoption Framework”, Procedia Computer Science 94 (2016), pp 485-490
  16. S.A. Hussain, M.Fatima, A. Saeed, I. Raza, R. K. Shahzad, “Multilevel classification of security concerns in cloud computing”, Applied Computing and Informatics, 2210-8327, 2016, King Saud University Published by Elsevier B.V.
  17. C. Saadia, H. Chaouib, “Cloud Computing Security Using IDS-AM-Clust, Honeyd, Honeywall and Honeycomb”, Procedia Computer Science 85 (2016), pp 433-442
Index Terms

Computer Science
Information Sciences

Keywords

Multi-tenancy cloud Big Data Security Intruder Attack scalability.