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Design of Host based Intrusion Detection System using Fuzzy Inference Rule

by Hari Om, Alok Kumar Gupta
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 9
Year of Publication: 2013
Authors: Hari Om, Alok Kumar Gupta
10.5120/10666-5442

Hari Om, Alok Kumar Gupta . Design of Host based Intrusion Detection System using Fuzzy Inference Rule. International Journal of Computer Applications. 64, 9 ( February 2013), 39-46. DOI=10.5120/10666-5442

@article{ 10.5120/10666-5442,
author = { Hari Om, Alok Kumar Gupta },
title = { Design of Host based Intrusion Detection System using Fuzzy Inference Rule },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 9 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 39-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number9/10666-5442/ },
doi = { 10.5120/10666-5442 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:15:59.675662+05:30
%A Hari Om
%A Alok Kumar Gupta
%T Design of Host based Intrusion Detection System using Fuzzy Inference Rule
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 9
%P 39-46
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The security of a system is an important issue due to the latest advancements in information technology. Intrusion Detection Systems are used to identify the attacks and malicious activities in the computer systems. This paper discusses a new host based intrusion detection system for detecting changes in hardware profile using fuzzy inference rule. The proposed system is able to analyze and detect the unauthorized access in a computer system by generating a set of fuzzy IF-THEN rules with the help of frequent item set. These fuzzy inference rules are used to find the misuse of the system. The experiments of the proposed system are carried out on the system performance log.

References
  1. Adetunmbi A. O. , Zhiwei S. , Zhongzhi S. , Adewale O. S. , "Network Anomalous Intrusion Detection using Fuzzy-Bayes," International Federation for Information Processing, Vol. 228, pp. 525-530, 2006.
  2. Biswanath, M. , Todd L. H. AND Karl, N. L. , "Network Intrusion Detection," IEEE Network, Vol. 8(3), pp. 26-41, 1994.
  3. Han J. , Pei J. , Yin Y. , Mao R. , "Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach," Data Mining and Knowledge Discovery, Vol. 8(1), pp. 53-87, 2004.
  4. Anderson J. P. , Computer Security Threat Monitoring and Surveillance. Technical report, Fort Washington, PA, Apr. 1980.
  5. Denning D. E. , "An Intrusion Detection Model," IEEE Trans. on Software Engineering, Vol. 13(2), pp. 222-232, 1987.
  6. Srinivasa K. G. , Chandra S. , Kajaria S. , Mukherjee S. , "IGIDS: Intelligent Intrusion Detection System Using Genetic Algorithms," World Congress on Information and Communication Technologies, pp. 852-857, 2011.
  7. Siraj M. M. , Maarof M. A. , Hashim S. Z. M. , "Intelligent Alert Clustering Model for Network Intrusion Analysis," Int. J. Advance Soft Comput. Appl. Vol. 1 (1), pp. 33-48, 2009.
  8. Shanmugavadivu R. , Nagarajan N. , "An Anomaly Based Netwok Intrusion Detection System Using Fuzzy logic," IJCSIS, Vol. 8(8), pp. 185-193, 2010.
  9. Dhanalakshmi Y. , Babu I. R. , "Intrusion Detection Using Data Mining Along Fuzzy Logic and Genetic Algorithms," IJCSNS, Vol. 8(2), pp. 27-32, 2008.
  10. Om H. , Hazra T. , "Design of Anomaly Detection System for Outlier Detection in Hardware Profile Using PCA," IJCSE, Vol. 4(9), pp. 1623-1632, 2012.
  11. Bharti K. , Jain S. , Shukla S. , "Fuzzy K-mean Clustering Via J48 For Intrusion Detection System," IJCSIT, Vol. 1(4), pp. 315-318, 2010.
  12. Han S. J. , Cho S. B. , "Evolutionary Neural Network for Anomaly Detection Based on the Behaviour of a Program," IEEE Trans. on Systems, Man and Cybernetics-Part B, Vol. 36(3), pp. 559-570, 2006.
  13. Om H. , Sarkar T. K. , "Neural network based intrusion detection system for detecting changes in hardware profile," Journal of Discrete Mathematics and Cryptography, Vol. 12(4), pp. 451-466, 2009.
  14. Mamdani, E. H. and S. Assilian, "An experiment in linguistic synthesis with a fuzzy logic controller," Int. Journal of Man-Machine Studies, Vol. 7(1), pp. 1-13, 1975.
  15. Stallings, W. Cryptography and Network Security Principles and Practices: Prentice Hall, 1998.
  16. Lamba,V. K. , Neuro Fuzzy System, University Science press: 2008
  17. Zadeh, L. A. , "Outline of a new approach to the analysis of complex systems and decision processes," IEEE Trans. on Systems, Man, and Cybernetics, Vol. 3(1), pp. 28-44, 1973.
  18. Cirstea, Dinu A. , Khor, Mccormick M. , Neural and Fuzzy logic control of Drives and Power System, Elsevier : 2002
Index Terms

Computer Science
Information Sciences

Keywords

Intrusion Detection System (IDS) Fuzzy logic System performance log Fuzzy inference rules

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