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Packet identification by using data mining techniques
Joint Authors
Ali, Ali Husayn
al-Mamuri, Safa Ubays Mahdi
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 24, Issue 3 (30 Sep. 2016), pp.565-579, 15 p.
Publisher
Publication Date
2016-09-30
Country of Publication
Iraq
No. of Pages
15
Main Subjects
Abstract EN
Accurate internet traffic identification and classification are fundamental to numerous network activities, including network management and security monitoring, traffic modeling and network planning, accounting and quality of service provision.
with the development of network, p2p as new generation of network technology is widely used.
starting from the first popular one (napster), a number of new p2p based multimedia file sharing systems have been developed (FastTrack, eDonkey, Gnutella, Direct Connect, etc.).
a fundamental types of networks architectures in today's world are client/ server and peer to peer.
a promising approach that has recently received some attention is traffic classification using machine learning techniques.
the term data mining is used for methods and algorithms that allow analyzing data in order to find rules and patterns describing the characteristic properties of the data.
the aim of this research is to classify traffic accuracy which can be achieved by using machine learning techniques such as K-Means and birch algorithms.
this system depends on the extracted attributes and then use it in the proposed system to distinguish all types of packets.
the goal of system of packet identification is to detect the types of packets and identification of application usage and trends , also identification of emerging applications diagnosing anomalies is critical for both network operators and end user in term of data security and service availability.
American Psychological Association (APA)
al-Mamuri, Safa Ubays Mahdi& Ali, Ali Husayn. 2016. Packet identification by using data mining techniques. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 24, no. 3, pp.565-579.
https://search.emarefa.net/detail/BIM-1347736
Modern Language Association (MLA)
al-Mamuri, Safa Ubays Mahdi& Ali, Ali Husayn. Packet identification by using data mining techniques. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 24, no. 3 (2016), pp.565-579.
https://search.emarefa.net/detail/BIM-1347736
American Medical Association (AMA)
al-Mamuri, Safa Ubays Mahdi& Ali, Ali Husayn. Packet identification by using data mining techniques. Journal of Babylon University : Journal of Applied and Pure Sciences. 2016. Vol. 24, no. 3, pp.565-579.
https://search.emarefa.net/detail/BIM-1347736
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 578-579
Record ID
BIM-1347736