Efficient intrusion detection scheme based on SVM
Article
Article Title | Efficient intrusion detection scheme based on SVM |
---|---|
ERA Journal ID | 40962 |
Article Category | Article |
Authors | Zhou, Guangping (Author) and Shrestha, Anup (Author) |
Journal Title | Journal of Networks |
Journal Citation | 8 (9), pp. 2128-2134 |
Number of Pages | 7 |
Year | 2013 |
Publisher | Academy Publisher |
Place of Publication | Oulu, Finland |
ISSN | 1796-2056 |
Digital Object Identifier (DOI) | https://doi.org/10.4304/jnw.8.9.2128-2134 |
Web Address (URL) | http://ojs.academypublisher.com/index.php/jnw/article/view/jnw080921282134 |
Abstract | The network intrusion detection problem is the focus of current academic research. In this paper, we propose to use Support Vector Machine (SVM) model to identify and detect the network intrusion problem, and simultaneously introduce a new optimization search method, referred to as Improved Harmony Search (IHS) algorithm, to determine the parameters of the SVM model for better classification accuracy. Taking the general mechanism network system of a growing city in China between 2006 and 2012 as the sample, this study divides the mechanism into normal network system and crisis network system according to the harm extent of network intrusion. We consider a crisis network system coupled with two to three normal network systems as paired samples. Experimental results show that SVMs based on IHS have a high prediction accuracy which can perform prediction and classification of network intrusion detection and assist in guarding against network intrusion. |
Keywords | support vector machine; SVM; improved harmony search; HIS; intrusion detection; comprehensive evaluation |
ANZSRC Field of Research 2020 | 460609. Networking and communications |
490406. Lie groups, harmonic and Fourier analysis | |
460499. Cybersecurity and privacy not elsewhere classified | |
Public Notes | © 2013 ACADEMY PUBLISHER. Open Access journal. Users are free to read, download, copy, distribute, print, search, or link to the full texts of these articles. |
Byline Affiliations | Zhejiang University of Science and Technology, China |
School of Information Systems | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q212y/efficient-intrusion-detection-scheme-based-on-svm
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