Network anomaly detection approach based on frequent pattern mining technique

With the tremendous growth of shopping, banking, and other business transactions over computers network in the last two decades, The number of potential cyber-attacks by intruders has increased. Therefore the efforts are continually required in order to improve the effectiveness of detecting the net...

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Main Authors: Dominic, D.D., Said, A.M.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31358 /
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946689632&doi=10.1109%2fICCST.2014.7045011&partnerID=40&md5=78c860e4231bac3bff69ba73b56bab6a
http://eprints.utp.edu.my/31358/
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id utp-eprints.31358
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spelling utp-eprints.313582022-03-25T09:06:49Z Network anomaly detection approach based on frequent pattern mining technique Dominic, D.D. Said, A.M. With the tremendous growth of shopping, banking, and other business transactions over computers network in the last two decades, The number of potential cyber-attacks by intruders has increased. Therefore the efforts are continually required in order to improve the effectiveness of detecting the network intruders. In this paper, a new network anomaly detection approach, which is based on outlier detection scheme, is presented. The frequent patterns are exploited for modeling the normal behavior of the traffic data and for calculating the deviation of the current traffic data points. The experimental results on KDD99 data set demonstrate the effectiveness of the propose approach in comparison with existing methods. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946689632&doi=10.1109%2fICCST.2014.7045011&partnerID=40&md5=78c860e4231bac3bff69ba73b56bab6a Dominic, D.D. and Said, A.M. (2014) Network anomaly detection approach based on frequent pattern mining technique. In: UNSPECIFIED. http://eprints.utp.edu.my/31358/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description With the tremendous growth of shopping, banking, and other business transactions over computers network in the last two decades, The number of potential cyber-attacks by intruders has increased. Therefore the efforts are continually required in order to improve the effectiveness of detecting the network intruders. In this paper, a new network anomaly detection approach, which is based on outlier detection scheme, is presented. The frequent patterns are exploited for modeling the normal behavior of the traffic data and for calculating the deviation of the current traffic data points. The experimental results on KDD99 data set demonstrate the effectiveness of the propose approach in comparison with existing methods. © 2014 IEEE.
format Conference or Workshop Item
author Dominic, D.D.
Said, A.M.
spellingShingle Dominic, D.D.
Said, A.M.
Network anomaly detection approach based on frequent pattern mining technique
author_sort Dominic, D.D.
title Network anomaly detection approach based on frequent pattern mining technique
title_short Network anomaly detection approach based on frequent pattern mining technique
title_full Network anomaly detection approach based on frequent pattern mining technique
title_fullStr Network anomaly detection approach based on frequent pattern mining technique
title_full_unstemmed Network anomaly detection approach based on frequent pattern mining technique
title_sort network anomaly detection approach based on frequent pattern mining technique
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946689632&doi=10.1109%2fICCST.2014.7045011&partnerID=40&md5=78c860e4231bac3bff69ba73b56bab6a
http://eprints.utp.edu.my/31358/
_version_ 1741197560187453440
score 11.62408

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