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MCA Based Anonymous DoS Attacks Detection

S.Avinash 1 , Y.Ramakrishna 2 , J.Venkata Krishna3

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-5 , Page no. 258-260, May-2015

Online published on May 30, 2015

Copyright © S.Avinash, Y.Ramakrishna , J.Venkata Krishna . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: S.Avinash, Y.Ramakrishna , J.Venkata Krishna, “MCA Based Anonymous DoS Attacks Detection,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.5, pp.258-260, 2015.

MLA Style Citation: S.Avinash, Y.Ramakrishna , J.Venkata Krishna "MCA Based Anonymous DoS Attacks Detection." International Journal of Computer Sciences and Engineering 3.5 (2015): 258-260.

APA Style Citation: S.Avinash, Y.Ramakrishna , J.Venkata Krishna, (2015). MCA Based Anonymous DoS Attacks Detection. International Journal of Computer Sciences and Engineering, 3(5), 258-260.

BibTex Style Citation:
@article{Krishna_2015,
author = {S.Avinash, Y.Ramakrishna , J.Venkata Krishna},
title = {MCA Based Anonymous DoS Attacks Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2015},
volume = {3},
Issue = {5},
month = {5},
year = {2015},
issn = {2347-2693},
pages = {258-260},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=514},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=514
TI - MCA Based Anonymous DoS Attacks Detection
T2 - International Journal of Computer Sciences and Engineering
AU - S.Avinash, Y.Ramakrishna , J.Venkata Krishna
PY - 2015
DA - 2015/05/30
PB - IJCSE, Indore, INDIA
SP - 258-260
IS - 5
VL - 3
SN - 2347-2693
ER -

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Abstract

All well organized systems, for example, net servers, document servers, distributed computing and so on… are presently under genuine attacks from system assailants. Denial of service attack is the standout amongst the most successive and forceful to processing frameworks. In this plan we propose a methodology called multivariate relationship investigation to distinguish an accurate movement stream characterization by separating the geometrical connection between known and obscure assaults. This framework incorporates abnormality recognition strategy for the identification of known and obscure Dos. Moreover Triangle Area Based method is utilized to accelerate the procedure of Multivariate Correlation Analysis (MCA). Proposed framework can be assessed by utilizing KDD cup dataset.

Key-Words / Index Term

Dos Attack Detection,Multi Variate Correlation Analysis

References

[1] V. Paxson, “Bro: A System for Detecting Network Intruders in Real-Time,” Computer Networks, vol. 31, pp. 2435-2463, 1999.
[2] P. Garca-Teodoro, J. Daz-Verdejo, G. Maci-Fernndez, and E. Vzquez, “Anomaly-Based Network Intrusion Detection: Techniques, Systems and Challenges,” Computers and Security, vol. 28, pp. 18-28, 2009.
[3] K. Lee, J. Kim, K.H. Kwon, Y. Han, and S. Kim, “DDoS Attack Detection Method Using Cluster Analysis,” Expert Systems with Applications, vol. 34, no. 3, pp. 1659-1665, 2008.
[4] A. Tajbakhsh, M. Rahmati, and A. Mirzaei, “Intrusion Detection Using Fuzzy Association Rules,” Applied Soft Computing, vol. 9, no. 2, pp. 462-469, 2009.
[5] C. Yu, H. Kai, and K. Wei-Shinn, “Collaborative Detection of DDoS Attacks over Multiple Network Domains,” IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 12, pp. 1649-1662, Dec.2007.
[6] J. Yu, H. Lee, M.-S. Kim, and D. Park, “Traffic Flooding Attack Detection with SNMP MIB Using SVM,” Computer Comm., vol. 31, no. 17, pp. 4212-4219, 2008.
[7] Z. Tan, A. Jamdagni, X. He, P. Nanda, and R.P. Liu, “Triangle- Area-Based Multivariate Correlation Analysis for Effective Denialof-Service Attack Detection,” Proc. IEEE 11th Int’l Conf. Trust, Security and Privacy in Computing and Comm., pp. 33-40, 2012.
[8] G. Thatte, U. Mitra, and J. Heidemann, “Parametric Methods for Anomaly Detection in Aggregate Traffic,” IEEE/ACM Trans. Networking, vol. 19, no. 2, pp. 512-525, Apr. 2011.