Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications

Internet traffic classification gained significant attention in the last few years. Most of the current classification methods were only valid for offline classification. The three common classification methods i.e. port, payload and statistics based have some limitations. This paper exploits the a...

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Main Authors: Hamza Awad, Hamza Ibrahim, Sulaiman, Mohd Nor, Izzeldin, I. Mohd, Mohamed Saad, Mahoub, Haitham, A. Jamil
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/8295/1/Real-time_Traffic_Classification_Algorithm_Based_on_Hybrid_of_Signature_Statistical_and_Port_to_Identify_Internet_Applications.pdf
http://umpir.ump.edu.my/id/eprint/8295/
http://dx.doi.org/10.1109/ISMS.2014.117
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spelling my.ump.umpir.82952021-09-03T08:43:29Z http://umpir.ump.edu.my/id/eprint/8295/ Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications Hamza Awad, Hamza Ibrahim Sulaiman, Mohd Nor Izzeldin, I. Mohd Mohamed Saad, Mahoub Haitham, A. Jamil TK Electrical engineering. Electronics Nuclear engineering Internet traffic classification gained significant attention in the last few years. Most of the current classification methods were only valid for offline classification. The three common classification methods i.e. port, payload and statistics based have some limitations. This paper exploits the advantages of all the three methods by combining them to produce a new classification algorithm called SSPC (Signature Statistical Port Classifier). In the proposed algorithm, each of the three classifiers will individually classify the same traffic flow. Based on certain priority rules, SSPC makes classification decisions for each flow. The SSPC algorithm was used to classifying four types of Internet applications in two stages, initially offline and later online. The results of both cases show that SSPC is the higher accuracy when compared with other classifiers. In addition, as demonstrated in the real time online experiments done, SSPC algorithm uses a short time to classify traffic and thus it is suitable to be used for online classification. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/8295/1/Real-time_Traffic_Classification_Algorithm_Based_on_Hybrid_of_Signature_Statistical_and_Port_to_Identify_Internet_Applications.pdf Hamza Awad, Hamza Ibrahim and Sulaiman, Mohd Nor and Izzeldin, I. Mohd and Mohamed Saad, Mahoub and Haitham, A. Jamil (2014) Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications. In: Fifth International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2014), 27-29 January 2014 , Sheraton Langkawi Beach Resort Teluk Nibong Langkawi, Kedah. pp. 652-657.. http://dx.doi.org/10.1109/ISMS.2014.117
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Hamza Awad, Hamza Ibrahim
Sulaiman, Mohd Nor
Izzeldin, I. Mohd
Mohamed Saad, Mahoub
Haitham, A. Jamil
Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
description Internet traffic classification gained significant attention in the last few years. Most of the current classification methods were only valid for offline classification. The three common classification methods i.e. port, payload and statistics based have some limitations. This paper exploits the advantages of all the three methods by combining them to produce a new classification algorithm called SSPC (Signature Statistical Port Classifier). In the proposed algorithm, each of the three classifiers will individually classify the same traffic flow. Based on certain priority rules, SSPC makes classification decisions for each flow. The SSPC algorithm was used to classifying four types of Internet applications in two stages, initially offline and later online. The results of both cases show that SSPC is the higher accuracy when compared with other classifiers. In addition, as demonstrated in the real time online experiments done, SSPC algorithm uses a short time to classify traffic and thus it is suitable to be used for online classification.
format Conference or Workshop Item
author Hamza Awad, Hamza Ibrahim
Sulaiman, Mohd Nor
Izzeldin, I. Mohd
Mohamed Saad, Mahoub
Haitham, A. Jamil
author_facet Hamza Awad, Hamza Ibrahim
Sulaiman, Mohd Nor
Izzeldin, I. Mohd
Mohamed Saad, Mahoub
Haitham, A. Jamil
author_sort Hamza Awad, Hamza Ibrahim
title Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
title_short Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
title_full Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
title_fullStr Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
title_full_unstemmed Real-time Traffic Classification Algorithm Based on Hybrid of Signature Statistical and Port to Identify Internet Applications
title_sort real-time traffic classification algorithm based on hybrid of signature statistical and port to identify internet applications
publishDate 2014
url http://umpir.ump.edu.my/id/eprint/8295/1/Real-time_Traffic_Classification_Algorithm_Based_on_Hybrid_of_Signature_Statistical_and_Port_to_Identify_Internet_Applications.pdf
http://umpir.ump.edu.my/id/eprint/8295/
http://dx.doi.org/10.1109/ISMS.2014.117
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