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Designing an accurate and efficient classification approach for network traffic monitoring
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TLDR
In recent years, knowing what information is passing through the networks is rapidly becoming more and more complex due to the ever-growing list of applications shaping today's Internet traffic.Abstract:
In recent years, knowing what information is passing through the networks is rapidly becoming more and more complex due to the ever-growing list of applications shaping today's Internet traffic. Consequently, traffic monitoring and analysis have become crread more
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Journal ArticleDOI
Edge Computing Intelligence Using Robust Feature Selection for Network Traffic Classification in Internet-of-Things
Bushra Mohammed,Mosab Hamdan,Joseph Stephen Bassi,Haitham A. Jamil,Suleman Khan,Abdallah Elhigazi,Danda B. Rawat,Ismahani Ismail,Muhammad Nadzir Marsono +8 more
TL;DR: The overall performance indicates that EWA-selected statistical flow features can improve the overall traffic classification, and the smaller number of features directly contributes to shorter classification time.
Journal ArticleDOI
Bit vector-coded simple CART structure for low latency traffic classification on FPGAs
TL;DR: A novel data structure, named Bit Vector Coded Simple CART (BC-SC), for ML based internet traffic classification is proposed, which is a scalable solution in terms of the number of application classes while providing a significant improvement in search latency, memory requirement and throughput when compared to the state-of-the-art approaches.
Journal ArticleDOI
Comparative Analysis of Machine Learning techniques for Network Traffic Classification
TL;DR: It is recommended that feature selection be included in the network classification process to guarantee an optimal accuracy result and reflects the importance of applying only relevant and non-redundant features to the ML methods.
References
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