Using Burstiness for Network Applications Classification
Joint Authors
Bakhshi, Taimur
Ghita, Bogdan
Oudah, Hussein
Alruban, Abdulrahman
Walker, David J.
Source
Journal of Computer Networks and Communications
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Network traffic classification is a vital task for service operators, network engineers, and security specialists to manage network traffic, design networks, and detect threats.
Identifying the type/name of applications that generate traffic is a challenging task as encrypting traffic becomes the norm for Internet communication.
Therefore, relying on conventional techniques such as deep packet inspection (DPI) or port numbers is not efficient anymore.
This paper proposes a novel flow statistical-based set of features that may be used for classifying applications by leveraging machine learning algorithms to yield high accuracy in identifying the type of applications that generate the traffic.
The proposed features compute different timings between packets and flows.
This work utilises tcptrace to extract features based on traffic burstiness and periods of inactivity (idle time) for the analysed traffic, followed by the C5.0 algorithm for determining the applications that generated it.
The evaluation tests performed on a set of real, uncontrolled traffic, indicated that the method has an accuracy of 79% in identifying the correct network application.
American Psychological Association (APA)
Oudah, Hussein& Ghita, Bogdan& Bakhshi, Taimur& Alruban, Abdulrahman& Walker, David J.. 2019. Using Burstiness for Network Applications Classification. Journal of Computer Networks and Communications،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1172341
Modern Language Association (MLA)
Oudah, Hussein…[et al.]. Using Burstiness for Network Applications Classification. Journal of Computer Networks and Communications No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1172341
American Medical Association (AMA)
Oudah, Hussein& Ghita, Bogdan& Bakhshi, Taimur& Alruban, Abdulrahman& Walker, David J.. Using Burstiness for Network Applications Classification. Journal of Computer Networks and Communications. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1172341
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1172341