#5, First Floor, 4th Street , Dr. Subbarayan Nagar, Kodambakkam, Chennai-600 024 pro@slogix.in

Office Address

  • #5, First Floor, 4th Street Dr. Subbarayan Nagar Kodambakkam, Chennai-600 024 Landmark : Samiyar Madam
  • pro@slogix.in
  • +91- 81240 01111

Social List

Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm - 2018

Author(s) Name:  Mohammed A. Ambusaidi; Xiangjian He; Priyadarsi Nanda and Zhiyuan Tan
Journal name:  IEEE Transactions on Computers
Conferrence name:  
Publisher name:  IEEE
DOI:  10.1109/TC.2016.2519914
Research Area:  Machine Learning
Abstract:

Redundant and irrelevant features in data have caused a long-term problem in network traffic classification. These features not only slow down the process of classification but also prevent a classifier from making accurate decisions, especially when coping with big data. In this paper, we propose a mutual information based algorithm that analytically selects the optimal feature for classification. This mutual information based feature selection algorithm can handle linearly and nonlinearly dependent data features. Its effectiveness is evaluated in the cases of network intrusion detection. An Intrusion Detection System (IDS), named Least Square Support Vector Machine based IDS (LSSVM-IDS), is built using the features selected by our proposed feature selection algorithm. The performance of LSSVM-IDS is evaluated using three intrusion detection evaluation datasets, namely KDD Cup 99, NSL-KDD and Kyoto 2006+ dataset. The evaluation results show that our feature selection algorithm contributes more critical features for LSSVM-IDS to achieve better accuracy and lower computational cost compared with the state-of-the-art methods.

Volume Information:  Volume: 65, Issue: 10, Oct. 1 2016,Page(s): 2986 - 2998
Journal Link:

https://ieeexplore.ieee.org/document/7387736