0% Complete
Home
/
12th International Conference on Computer and Knowledge Engineering
The Effect of Network Environment on Traffic Classification
Authors :
Abolghasem Rezaei Khesal
1
Mehdi Teimouri
2
1- University of Tehran
2- University of Tehran
Keywords :
Robust traffic classification،machine learning،feature engineering،cross-validation،network traffic dataset
Abstract :
One of the challenges of network traffic classification and mobile app identification is model generalization. The accuracy and efficiency of classification models are strongly influenced by the network environment and user behavior. By changing the network environmental parameters such as mobile type or app version, the accuracy of the trained classification model may be reduced. In this paper, we investigate the effect of the network environment on one of the most well-known networks traffic classifiers. To this end, we have collected a dataset of 60 popular apps in Iran using different network environments.
Papers List
List of archived papers
Robust Learning to Learn Graph Topologies
Navid Akhavan Attar - Ali Fahim
FarCQA: A Farsi Community Dataset for Question Classification and Answer Selection
Saba Emami - Maedeh Mosharraf
SGFL: A Federated Learning Approach for Non-IID Data Using Semi-Supervised DCGAN
Alireza Rabiee - Abolfazl Ajdarloo - Mohsen Rahmani
A Novel Hybrid Method for Clustering Text Documents using Evolutionary Optimization
Muhammad Naderi - Maryam Amiri
SingAll: Scalable Control Flow Checking for Multi-Process Embedded Systems
Mehdi Amininasab - Ahmad Patooghy - Mahdi Fazeli
Disturbance Rejection in Quadruple-Tank System by Proposing New Method in Reinforcement Learning
Alireza Nezamzadeh - Mohammadreza Esmaeilidehkordi
Segmentation of Hard Exudates in Retinal Fundus Images Using BCDU-Net
Nafise Ameri - Nasser Shoeibi - Mojtaba Abrishami
Community-Based QoE Enhancement for User-Generated Content Live Streaming
Reza Saeedinia - S.Omid Fatemi - Daniele Lorenzi - Farzad Tashtarian - Christian Timmerer
Spatio-Temporal Graph Neural Networks for Accurate Crime Prediction
Rojan Roshankar - Mohammad Reza Keyvanpour
A Deep Reinforcement Learning Approach Combining Technical and Fundamental Analyses with a Large Language Model for Stock Trading
Mahan Veisi - Sadra Berangi - Mahdi Shahbazi Khojasteh - Armin Salimi-Badr
more
Samin Hamayesh - Version 42.4.1