Journal of Computer & Information Technology

Intrusion Detection Using Data Mining Along Fuzzy Logic & Genetic Algorithms

Author & Affiliation:
RUCHI CHATURVEDI
M. Tech Scholar, Department of Computer Science & Engineering, Lakshmi Narain College of Technology & Excellence Bhopal (M.P.), (India)
BABITA PATHIK
Assistant Professor, Department of CSE, Lakshmi Narain College of Technology & Excellence, Bhopal (M.P) (India)
SHIV KUMAR
Professor & Head, Department of CSE, Lakshmi Narain College of Technology & Excellence, Bhopal (M.P), (India)
Keyword:
Unsupervised Machine Learning, Network Intrusion Detection, Network Security, genetic algorithm
Issue Date:
February 2018
Abstract:
Network security is of primary concerned now days for large organizations. The intrusion detection systems (IDS) are becoming indispensable for effective protection against attacks that are constantly changing in magnitude and complexity. With data integrity, confidentiality and availability, they must be reliable, easy to manage and with low maintenance cost. Various modifications are being applied to IDS regularly to detect new attacks and handle them. This paper proposes a fuzzy genetic algorithm (FGA) for intrusion detection. The FGA system is a fuzzy classifier, whose knowledge base is modelled as a fuzzy rule such as “if-then” and improved by a genetic algorithm. The reasons for introducing fuzzy logic is twofold, the first being the involvement of many quantitative features where there is no separation between normal operations and anomalies. Thus fuzzy association rules can be mined to find the abstract correlation among different security features. The method is tested on the benchmark KDD’99 intrusion dataset and compared with other existing techniques available in the literature. The results are encouraging and demonstrate the benefits of the proposed approach.
Pages:
9-13
ISSN:
2455-9997 (Online) - 2229-3531 (Print)
Source:
DOI:
http://dx.doi.org/10.22147/jucit/090102

Copy the following to cite this article:

R. Chaturvedi; B. Pathik; S. Kumar, "Intrusion Detection Using Data Mining Along Fuzzy Logic & Genetic Algorithms", Journal of Computer & Information Technology, Volume 9, Issue 1, Page Number 9-13, 2018

Copy the following to cite this URL:

R. Chaturvedi; B. Pathik; S. Kumar, "Intrusion Detection Using Data Mining Along Fuzzy Logic & Genetic Algorithms", Journal of Computer & Information Technology, Volume 9, Issue 1, Page Number 9-13, 2018

Available from: http://www.compitjournal.org/paper/351/

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