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...

Accurate network traffic identification plays important roles in many areas such as traffic engineering, QoS and intrusion detection etc. The emergence of many new encrypted applications which use dynamic port numbers and masquerading techniques causes the most challenging problem in network traffic identification field. One of the challenging issues for existing traffic identification methods ...

In recent years, many machine learning methods have been used in network traffic identification.In order to improve the accuracy and solve some problems of network traffic identification, this paper presents a multi layer perceptron neural network-based method for network traffic identification, and parameters of multi-layer perceptron neural network are analyzed. Experimental results show that...

Abstract: Traffic identification is a key task for any Internet Service Provider (ISP) or network administrator. Machine learning method is an important research method on traffic identification, while impact of the asymmetry router on the traffic identification is considered, so this paper analyzes the impact of asymmetry routing on traffic identification, and proposes an effective method to d...

Network traffic classification is extensively required mainly for many network management tasks such as flow prioritization, traffic shaping/policing, and diagnostic monitoring. Similar to network management tasks, many network engineering problems such as workload characterization and modeling, capacity planning, and route provisioning also benefit from accurate identification of network traff...

Network traffic classification has become significantly important with rapid growth of current Internet network and online applications. There have been numerous studies on this topic which have led to many different approaches. Most of these approaches use predefined features extracted by an expert in order to classify network traffic. In contrast, in this study, we propose a deep learning bas...

Network technology plays an increasingly important role in all aspects of social life. The Internet has brought a new round industrial revolution and upgrading. arrival the “Internet” era is accompanied by large-scale increase network applications number netizens. At same time, severity cyberattacks continue to increase. Therefore, intrusion detection systems (IDSs) have become part current sec...