CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
Implementation of Feature Selection Using Correlation Matrix in Python

Ahmad Farhan AlShammari
Random Articles
Reseach Article

Classifier System in Cloud Environment to Detect Denial of Service Attack

by Wafa' Slaibi Alsharafat
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 14
Year of Publication: 2014
Authors: Wafa' Slaibi Alsharafat
10.5120/14908-3455

Wafa' Slaibi Alsharafat . Classifier System in Cloud Environment to Detect Denial of Service Attack. International Journal of Computer Applications. 85, 14 ( January 2014), 13-17. DOI=10.5120/14908-3455

@article{ 10.5120/14908-3455,
author = { Wafa' Slaibi Alsharafat },
title = { Classifier System in Cloud Environment to Detect Denial of Service Attack },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 14 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number14/14908-3455/ },
doi = { 10.5120/14908-3455 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:02:26.353426+05:30
%A Wafa' Slaibi Alsharafat
%T Classifier System in Cloud Environment to Detect Denial of Service Attack
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 14
%P 13-17
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is a modern style of computer services. This system has some of similarities with distributed systems, through using network environment features. Therefore the security is one of most critical issues in this type of environment. Because of vast number of users become connected to the network with times, the opportunity for malicious users or an attack to perform damage actions becomes very great and profitable. One of the major security challenges in cloud environment is the detection of any attempts of intrusions and attacks. In order to detect these malicious activities especially Denial of Service (DoS) attack, this paper will propose Learning Classifier System for Intrusion Detection System (LCS-IDS) to detect DoS in cloud environment attacks by taking advantage of learning from attacks themselves and simulate possible DoS attacks through Genetic Algorithm, generator, to rise detection rate compared with other systems in this field.

References
  1. Shaikh, R. , Sasikumar, M. 2012. Security Issues in Cloud Computing: A survey. International Journal of Computer Applications (0975 – 8887) Volume 44– No19. April 2012.
  2. Heady,R. , George, L. , Maccabe, A. , and Servilla, M. 1990. The Architecture of a Network Level Intrusion Detection System, Technical report, University of New Mexico.
  3. Bouzida Y. , Cuppens F. , Gombault S. 2006. Detecting and Reacting against Distributed Denial of Service Attacks. IEEE International Conference on Communication. Volume 5.
  4. Meiko Jensen, Jorg Schwenk, Nils Gruschka, Luigi Lo Iacon. 2009. On technical Security Issues in Cloud Computing. Proc. of IEEE International Conference on Cloud Computing (CLOUD-II, 2009), pp. 109-116, India, 2009.
  5. Olive, Ch. 2011. Cloud Computing Characteristics Are Key. © General Physics Corporation 2011.
  6. Ram,S. , Velmurugan,Thirukumaran. 2012. Effective Analysis of Cloud Based Intrusion Detection System. International Journal of Computer Applications & Information Technology Vol. I, Issue II, September, 2012 (ISSN: 2278- 7720).
  7. Dhage, S. N. , et al. 2011. Intrusion Detection System in Cloud Computing Environment. In International Conference and Workshop on Emerging Trends in Technology (ICWET 2011) ' TCET, Mumbai. India, pp. 235-239, 2011.
  8. Chi-Chun Lo, Chun-Chieh Huang,Joy Ku. 2010. A Cooperative Intrusion Detection System Framework for Cloud Computing Networks. 39th International Conference on Parallel Processing Workshops,2010,pp280-284.
  9. Singh, N. , S. Ghrera, and P. 2010 . Chaudhuri, Denial of Service Attack: Analysis of Network Traffic Anormaly using Queuing Theory. Arxiv preprint arXiv:1006. 2807, 2010.
  10. Yeung, D. S. , S. Jin, and X. Wang. 2007. Covariance-matrix modeling and detecting various flooding attacks. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 2007. 37(2): p. 157-169.
  11. Lo, C. C. , C. C. Huang, and J. Ku. 2010. A cooperative intrusion detection system framework for cloud computing Networks. 2010: IEEE.
  12. Holland, J. H. 1975. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. University of Michigan Press, Ann Arbor, MI.
  13. Lanzi, P. -L. 2002. Learning Classifier Systems from a Reinforcement Learning Perspective. Journal of Soft Computing, 6(3-4):162–170.
  14. Goldberg D. E. 1989. Genetic Algorithms: in search Optimization and Machine Learning, Adison Wesley, 1989.
  15. Forrest, S. & Miller, J. 1991. Emergent Behavior in Classifier Systems. Physica D 42: 213-217.
  16. KDD-CUP 1999 Data, http://kdd. ics. uci. edu/databases/kddcup99/kddcup99 . html.
  17. Alsharafat. W. 2010. Applying Artificial Neural Network and eXtended Classifier System for Network Intrusion Detection (ANNXCS-NID). The International Arab journal of Information Technology. Volume 10 No. 3.
  18. Alrashdan. W. Naoum. R. , ALsharafat. W. , Alkhazaaleh. M. 2010. An Integrated Model of Intrusion Detection Based on Hybrid Neural Network and Support Vector Machine. International Journal of Computer Science and Network Security. Vol. 10 No. 11 pp. 10-13
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing Intrusion Detection Denial of Service Learning Classifier System.

Powered by PhDFocusTM