Research on Online Game Traffic Classification Based on Machine Learning
نویسندگان
چکیده
This paper summarizes online game flow attributes by observing a great number of game data packets and computes their flow feature using Python programming language. Furthermore, we investigate several machine learning algorithms to classify five different online games automatically and correctly, that provide the average accuracy is over 80%. The test results show that machine learning has the better performance than the tradition method in classifying online game traffic. Keywords-game traffic, machine learning, flow atrributes
منابع مشابه
Classification of encrypted traffic for applications based on statistical features
Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applicat...
متن کاملBehavioral Analysis of Traffic Flow for an Effective Network Traffic Identification
Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...
متن کاملBody Mass Index Classification based on Facial Features using Machine Learning Algorithms for utilizing in Telemedicine
Background and Objectives: Due to the impact of controlling BMI on life, BMI classification based on facial features can be used for developing Telemedicine systems and eliminating the limitations of measuring tools, especially for paralyzed people. So that physicians can help people online during the Covid-19 pandemic. Method: In this study, new features and some previous work features were e...
متن کاملEvaluating Machine Learning Methods for Online Game Traffic Identification
Online gaming is becoming more and more prominent in the Internet, in terms of both traffic volume and as a potential source of revenue. Quality of Service (QoS) requirements for highly interactive games are much stricter than for traditional Internet applications, such as web or email. For effective QoS implementations that are transparent to users and game applications, an accurate and reliab...
متن کاملOnline Internet Traffic Classification Based on Proximal SVM
Online and accurate traffic classification is a key challenge for network management. Internet traffic classification based on flow statistics using machine learning method has attracted great attention. To solve the drawback of the previous classification scheme to meet the requirements of the network activities, our work mainly focuses on how to build an online Internet traffic classification...
متن کامل