DocumentCode :
1869059
Title :
On SPIM detection in LTE networks
Author :
Das, S. ; Pourzandi, Makan ; Debbabi, Mourad
Author_Institution :
Concordia Inst. for Inf. Syst. Eng., Concordia Univ., Montreal, QC, Canada
fYear :
2012
fDate :
April 29 2012-May 2 2012
Firstpage :
1
Lastpage :
4
Abstract :
The telecommunication enterprise networks are continuously facing increasing amount of messages and multi-media traffic due to growing deployment of messaging applications. The detection of SPAM over Instant Messaging (SPIM) is essential for the mobile service providers to achieve user satisfaction and efficient network load balancing. However, accurate SPIM detection is challenging at the server side due to large volume of data packets and near-real-time communication of messages. In this setting, we propose a message classification approach to collect valuable insight on SPIM inside LTE cellular telecommunication framework. The contribution of this paper is threefold: First, it identifies the location and scope of the SPIM detection component inside LTE architecture. Second, we compare the detection accuracy, training and testing time of different classification algorithms. Finally, we evaluate the additional delay in messaging for adding such a module inside LTE architecture using an OPNET simulation environment.
Keywords :
Long Term Evolution; multimedia communication; telecommunication traffic; LTE architecture; LTE cellular telecommunication framework; LTE networks; OPNET simulation environment; SPAM over instant messaging; SPIM detection; data packets; messaging applications; multimedia traffic; near-real-time communication; network load balancing; telecommunication enterprise networks; Accuracy; Computer architecture; Instant messaging; Mobile communication; Mobile computing; Protocols; Servers; Classification; LTE; Machine Learning; Mobile Network; SPIM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical & Computer Engineering (CCECE), 2012 25th IEEE Canadian Conference on
Conference_Location :
Montreal, QC
ISSN :
0840-7789
Print_ISBN :
978-1-4673-1431-2
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2012.6334959
Filename :
6334959
Link To Document :
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