Authors :
Mohsin Mahmood; Sohaib Ahmad Khalil; Syed Jamil Shah; Mansoor Ahmad
Volume/Issue :
Volume 8 - 2023, Issue 6 - June
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/f7z22mnr
DOI :
https://doi.org/10.5281/zenodo.8098744
Abstract :
This paper stresses the importance of network
traffic classification for ISPs in managing network
applications effectively. It provides a step-by-step
process for classification, using a real-time dataset and
four machine learning classifiers. The C4.5 classifier
achieves the highest accuracy among the tested
classifiers. Network traffic classification optimizes
performance, improves customer service, and enables
the detection of security threats. Machine learning,
particularly the C4.5 classifier, is effective in achieving
accurate results. Overall, network traffic classification is
crucial for ISPs, and machine learning techniques
enhance network performance and customer experience.
Keywords :
Traffic Classification; Machine Learning; Methods.
This paper stresses the importance of network
traffic classification for ISPs in managing network
applications effectively. It provides a step-by-step
process for classification, using a real-time dataset and
four machine learning classifiers. The C4.5 classifier
achieves the highest accuracy among the tested
classifiers. Network traffic classification optimizes
performance, improves customer service, and enables
the detection of security threats. Machine learning,
particularly the C4.5 classifier, is effective in achieving
accurate results. Overall, network traffic classification is
crucial for ISPs, and machine learning techniques
enhance network performance and customer experience.
Keywords :
Traffic Classification; Machine Learning; Methods.
