Network Traffic Classification for Detecting Multi-Activity Situations
Abstract
Network traffic classification is an active research
field that acts as an enabler for various applications in network
management and cybersecurity. Numerous studies from this field
have targeted the case of classifying network traffic into a
set of single-activities (e.g., chatting, streaming). However, the
proliferation of internet services and devices has led to the
emergence of new consuming patterns such as multi-tasking
that consists in performing several activities simultaneously.
Recognizing the occurrence of such multi-activity situations may
help service providers to design quality of service solutions
that better fit users’ requirements. In this paper, we propose a
framework that is able to recognize multi-activity situations based
on network traces. Our experiments showed that our solution is
able to achieve promising results despite the complexity of the
task that we target. Indeed, the obtained multi-activity detection
performance is equivalent or often surpasses state-of-the-art
techniques dealing with only a single activity.
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