Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

According to the problems of current distributed architecture intrusion detection systems (DIDS), a new online distributed intrusion detection model based on cellular neural network (CNN) was proposed, in which discrete-time CNN (DTCNN) was used as weak classifier in each local node and state-contro...

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Main Authors: Kang Xie, Yixian Yang, Yang Xin, Guangsheng Xia
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/343050
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spelling doaj-1cf6e69aafe24d2c9583c986030481a82020-11-24T21:37:20ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/343050343050Cellular Neural Network-Based Methods for Distributed Network Intrusion DetectionKang Xie0Yixian Yang1Yang Xin2Guangsheng Xia3College of Information Science and Engineering, Shandong University, Jinan 250100, ChinaCollege of Information Science and Engineering, Shandong University, Jinan 250100, ChinaInformation Security Center, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaNational Cybernet Security Ltd., Beijing 100088, ChinaAccording to the problems of current distributed architecture intrusion detection systems (DIDS), a new online distributed intrusion detection model based on cellular neural network (CNN) was proposed, in which discrete-time CNN (DTCNN) was used as weak classifier in each local node and state-controlled CNN (SCCNN) was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation which allows the distributed intrusion detection to be performed better.http://dx.doi.org/10.1155/2015/343050
collection DOAJ
language English
format Article
sources DOAJ
author Kang Xie
Yixian Yang
Yang Xin
Guangsheng Xia
spellingShingle Kang Xie
Yixian Yang
Yang Xin
Guangsheng Xia
Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
Mathematical Problems in Engineering
author_facet Kang Xie
Yixian Yang
Yang Xin
Guangsheng Xia
author_sort Kang Xie
title Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
title_short Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
title_full Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
title_fullStr Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
title_full_unstemmed Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection
title_sort cellular neural network-based methods for distributed network intrusion detection
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description According to the problems of current distributed architecture intrusion detection systems (DIDS), a new online distributed intrusion detection model based on cellular neural network (CNN) was proposed, in which discrete-time CNN (DTCNN) was used as weak classifier in each local node and state-controlled CNN (SCCNN) was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation which allows the distributed intrusion detection to be performed better.
url http://dx.doi.org/10.1155/2015/343050
work_keys_str_mv AT kangxie cellularneuralnetworkbasedmethodsfordistributednetworkintrusiondetection
AT yixianyang cellularneuralnetworkbasedmethodsfordistributednetworkintrusiondetection
AT yangxin cellularneuralnetworkbasedmethodsfordistributednetworkintrusiondetection
AT guangshengxia cellularneuralnetworkbasedmethodsfordistributednetworkintrusiondetection
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