Accurate application traffic classification and identification are important for network monitoring and analysis. The accuracy of traditional Internet application traffic classification approaches is rapidly decreasing due to the diversity of today’s Internet application traffic, such as ephemeral port allocation, proprietary protocol, and traffic encryption. This paper presents an empirical ev...

Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptabl...

Traffic classification is of fundamental importance to numerous other network activities, from security monitoring to accounting, and from Quality of Service to providing operators with useful forecasts for long-term provisioning. Naive Bayes estimator is applied to categorize the traffic by application. Uniquely, this work capitalizes on hand-classified network data, using it as input to a sup...

With the widespread use of encrypted data transport network traffic encryption is becoming a standard nowadays. This presents a challenge for traffic measurement, especially for analysis and anomaly detection methods which are dependent on the type of network traffic. In this paper, we survey existing approaches for classification and analysis of encrypted traffic. First, we describe the most w...

Network traffic classification is the basis of many network technologies including intrusion detection, traffic scheduling, and quality of service. Given the limitations of existing classification approaches based on the port number, the packet-payload and statistical characteristics of network traffic, in this paper we propose a novel classification method via a hidden Markov model. With the a...

Area of network traffic classification using application of machine learning has been increased enormously in recent years. Network traffic classificationis necessary today because of increase in no of users today in the internet and quality of service in the network. Network traffic classification algorithm works on various network traffic features. So in a huge amount of network traffic data ...

Accurate network traffic classification plays important roles in many areas such as traffic engineering, QoS and intrusion detection etc. Encrypted Peer-to-Peer (P2P) applications have dramatically grown in popularity over the past few years, and now constitute a significant share of the total traffic in many networks. To solve the drawback of the previous classification scheme for encrypted ne...

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SV...

The ability to accurately classify network traffic and to perform timely detection of the presence of unwanted classes of traffic has important implications for network operations and security. In recent years, classification has become more challenging due to applications that use ports that are not wellknown, that overload or masquerade with other applications’ well-known ports, and that may ...