Attribute Reduction for Effective Intrusion Detection

2004 ◽  
pp. 74-83 ◽  
Author(s):  
Fernando Godínez ◽  
Dieter Hutter ◽  
Raúl Monroy
Keyword(s):  
Intrusion Detection ◽  
Attribute Reduction

Network Intrusion Detection Method Based on RS-LSSVM

2014 ◽  
Vol 602-605 ◽  
pp. 1634-1637
Author(s):  
Fang Nian Wang ◽  
Shen Shen Wang ◽  
Wan Fang Che ◽  
Yun Bai
Keyword(s):  
Intrusion Detection ◽  
Detection Method ◽  
Attribute Reduction ◽  
Feature Space ◽  
Least Square ◽  
Classification Model ◽  
Network Intrusion Detection ◽  
Support Vector ◽  
Network Intrusion ◽  
Sample Data

An intrusion detection method based on RS-LSSVM is studied in this paper. Firstly, attribute reduction algorithm based on the generalized decision table is proposed to remove the interference features and reduce the dimension of input feature space. Then the classification method based on least square support vector machine (LSSVM) is analyzed. The sample data after dimension reduction is used for LSSVM training, and the LSSVM classification model is obtained, which forms the ability of detecting unknown intrusion. Simulation results show that the proposed method can effectively remove the unnecessary features and improve the performance of network intrusion detection.

A Case Study of Distributed Network Fault Detection Technology in Distance Education

2013 ◽  
Vol 760-762 ◽  
pp. 1282-1287
Author(s):  
Qian Jun Tang ◽  
Yan Zhang ◽  
Yong Ju Li
Keyword(s):  
Intrusion Detection ◽  
Pattern Matching ◽  
High Efficiency ◽  
Detection System ◽  
Attribute Reduction ◽  
Security Technology ◽  
Whole Process ◽  
Detection Technology ◽  
Network Fault

The intrusion detection under the environment of IPv6 is an important security technology along with firewall in system security defense system, which can be used for real-time detection and monitoring of the system in the whole process of system invasion. This paper puts forward an intrusion detection system under IPv6 platform based on intrusion detection feature attribute reduction by using pattern matching, so as to expand the range of application and user group of the security products. By the analysis and comparison of various pattern matching algorithms, the new algorithm realizes the intrusion feature module matching under IPv6, and make detection system be of high efficiency. Later experiments have proved this view.

Anomaly Intrusion Detection Based on Concept Lattice

2012 ◽  
Vol 220-223 ◽  
pp. 2388-2392
Author(s):  
Li Fang Wang
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection Rate ◽  
Detection System ◽  
Concept Lattice ◽  
Attribute Reduction ◽  
Training Data ◽  
Detection Model ◽  
Detection Technology ◽  
Anomaly Intrusion Detection

In order to identify potential and effective intrusion detection rules, and improve the detection rate of intrusion detection system, this paper combines the concept lattice with intrusion detection technology and proposes a anomaly intrusion detection system based on concept lattice theory. The system first pre-treats those collected data, regulates data and builds concept lattice using the minimal set of attributes which are obtained by attribute reduction. And it analyzes the implication relations between concepts and obtains non-redundant classification rules. The anomaly intrusion detection model based compared with other tests can easily get training data. Experimental results show the model reduces the computation amount to achieve classification, improves the intrusion detection rate and effectively controls the false detection rate.

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