bullet Sensors & Transducers Journal

    (ISSN 1726- 5479)

205.767

2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2013

Editorial Calendar 2013

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents

 

Best Articles 2011

 

 

 

Vol. 159, Issue 11, November 2013, pp. 230-235

 

Bullet

 

A Kind of Network Intrusion Detection Algorithm Based on Quantum-behaved Particle Swarm Optimization
 
1 Qiang Song, 2 Lingxia Liu

1 Anyang Institute of Technology, Anyang, 455000, China 2 Anyang Normal University , Anyang, 455000, China

1 E-mail: aysq168@163.com

 

Received: 24 August 2013   /Accepted: 25 October 2013   /Published: 30 November 2013

Digital Sensors and Sensor Sysstems

 

Abstract: In order to overcomes the drawbacks of fuzzy clustering methods which are sensitive to the initial values and easily trapped into local minima in intrusion detection algorithm, a hybrid algorithm is proposed based on quantum-behaved particle swarm optimization and semi-supervised kernel fuzzy clustering algorithm. This algorithm can supervise and clustering a few labeled data to generate correct model, use this model to guide lots of unlabeled data to clustering, and enlarge the labeled data set. Those data still cannot be labeled, which are clustered by the kernel fuzzy methods based on quantum-behaved particle swarm optimization, and determine mark types. The simulation of KDD CUP 99 data set is implemented to evaluate the proposed algorithm. Comparing to other algorithms, the result shows the proposed algorithm can obtain the ideal error detection rate and false drop rate in the intrusion detection.

 

Keywords: Intrusion detection, Quantum-behaved Particle Swarm Optimization (QPSO), Semi-supervised clustering, Kernel function.

 

 

Buy this article online (it will be send to you in the pdf format by e-mail) or subscribe Sensors & Transducers journal

(12 issues per year plus special issues; 40 % discount for payment IFSA Members):

 

 

Sensors & Transducers journal subscription

450 $ US per year:

 

Buy this article for
14.95 $ US:

 

 
 

 

 
 

Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com

 

Download <here> the Library Journal Recommendation Form

 

 

 

 

 


1999 - 2013 Copyright , International Frequency Sensor Association (IFSA). All Rights Reserved.


Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn