Jameel, M. A., Turner, S., Kanakis, T., Al-Sherbaz, A. and Bhaya, W. S. (2022) Deep Learning Approach for Real-time Video Streaming Traffic Classification. In: 2022 International Conference on Computer Science and Software Engineering (CSASE) :. IRQ: IEEE. pp. 168-174.
Al_Jameel_etal_IEEE_2022_Deep_Learning_Approach_for_Real-time_Video_Streaming_Traffic_Classification (7MB) |
| Item Type: | Book Section |
|---|---|
| Abstract: | Video streaming services such as Amazon Prime Video, Netflix and YouTube continue to be of enormous demand in everyday peoples' lives. This enticed research into new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Then, data was pre-processed to select the desired features for video traffic classification. Based on the performance evaluation, the model produces an overall accuracy of 99.3% when classifying video streaming traffic using a multi-layer feedforward neural network. This paper also evaluates the DL approach's effectiveness compared to the Gaussian Naive Bayes algorithm (GNB), one of the most well-known machine learning techniques used in Internet traffic classification. The model is promising to be applied in a real-time scenario as it showed its ability to predict new unseen data with 98.4 % overall accuracy. |
| Creators: | Jameel, Mohammed Al, Turner, Scott, Kanakis, Triantafyllos, Al-Sherbaz, Ali and Bhaya, Wesam S. |
| Publisher: | IEEE |
| Faculties, Divisions and Institutes: | Faculties > Faculty of Arts, Science & Technology > Computing |
| Date: | 25 April 2022 |
| Date Type: | Publication |
| Page Range: | pp. 168-174 |
| Title of Book: | 2022 International Conference on Computer Science and Software Engineering (CSASE) : |
| Series Name: | 2022 International Conference on Computer Science and Software Engineering (CSASE) |
| Event Title: | International Conference on Computer Science and Software Engineering (CSASE) |
| Event Dates: | 2022-03-15 - 2022-03-17 |
| Place of Publication: | IRQ |
| Event Location: | University of Duhok |
| Language: | English |
| ISBN: | 9781665426336 |
| DOI: | https://doi.org/10.1109/csase51777.2022.9759644 |
| Status: | Published / Disseminated |
| Refereed: | Yes |
| Related URLs: | |
| URI: | http://nectar.northampton.ac.uk/id/eprint/17002 |
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