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Network engineers and designers need additional tools to generate network traffic in order to test and evaluate, for instance, application performances or network provisioning. In such a context, traffic characteristics are the most important part of the work. Indeed, it is quite easy to generate traffic, but it is more difficult to produce traffic which can exhibit real characteristics such as the...
IP flow analysis is an effective way of doing network forensic analysis which aims to detect attack patterns and identify attackers in a given network traffic data. For attacks such as Distributed Denial of Service (DDoS), efficiently identifying the botnet in time can be a challenge. Recently, the unsupervised learning methods such as the K-means, self-organizing map (SOM), and growing hierarchical...
The advantage of graph-based anomaly detection is that the relationships between elements can be analyzed for structural oddities that could represent activities such as fraud, network intrusions, or suspicious associations in a social network. However, current approaches to detecting anomalies in graphs are computationally expensive and do not scale to large graphs. For instance, in the case of computer...
It has been reported that modeling a self-similar network traffic is of key importance for the traffic engineering. Self-similarity or long range dependence causes degradation of Internet router performance. Therefore, it is decisive for an appropriate buffer design of a router. In this paper, we investigate loss behaviour of network router with pseudo self-similar traffic input. We use Fractal point...
The evolution of Internet is continually growing, most people use online streaming applications to watch videos. However, some of P2P streaming applications usually occupy the network bandwidth, and the encrypted tunnel is usually used to avoid the traffic to be detected. Thus, it is an important issue for ISP to detect the traffic in the encrypted tunnel. This paper proposes a novel solution to detect...
Classification of network traffic is extensively required mainly for many network management tasks such as flow prioritization, traffic shaping/policing, and diagnostic monitoring. Many approaches have been evolved for this purpose. The classical approaches such as port number or payload analyis methods has their own limitations. For example, some applications uses dynamic port number and encryption...
Flood attacks are common threats to Internet, which has necessitated the need for visual analysis within an intrusion detection system to identify these attacks patterns. The challenges are how to increase the accuracy of detection and how to visualize and present the patterns of flood attack for early detection. In this paper, we introduce a Two-Density model that contains two coefficients: sending-density...
The current Internet model has proved more sustainable then the provisioned capacity at the time when the architecture was designed. The voluminous growth of traffic over the Internet has brought challenges for the exiting networking architecture. The information centric paradigm appears to offer efficient solution towards content dissemination model. It is a content-focused networking paradigm rather...
With the rapid rising of the number of cellular phone users, accessing the Internet via mobile device is becoming a new norm in terms of network activities and people's daily life, resulting in an ever-increasing usage of the mobile Internet. This paper analyze Service Provider (SP) traffic characteristics Based on the massive data collected from a commercial Internet Service Provider (ISP) covering...
The recent years have seen extensive work on statistics-based network traffic classification using machine learning (ML) techniques. In the particular scenario of learning from unlabeled traffic data, some classic unsupervised clustering algorithms (e.g. K-Means and EM) have been applied but the reported results are unsatisfactory in terms of low accuracy. This paper presents a novel approach for...
We report the results of a search for anomalies in network traffic. Our data set consisted of two billion packets collected over four days at the gateways of our large corporate network. Analysis of the distributions of the packet metadata fields (IP addresses, ports, time-to-live and packet length) revealed anomalous activity including IP scans, port scans and hybrid scans as well as coordinated...
Internet traffic monitoring and analysis have been a very essential way in network management and optimization for the ISP. GPRS networks are increasingly carrying Internet traffic for Web browsing, Email and online games etc. In this paper, we proposed a Hadoop based cloud computing platform for high-speed network traffic analysis. We experimentally prove that our platform is capable of analyzing...
Symbol based applications are aimed for alternative and augmentative communication and education of persons with complex communication needs. Since available symbol galleries typically contain huge number of symbols that are graphical representations of words, and since one of the favorable user requirements is that application supports multiple symbol galleries, a problem of presenting a subset of...
Internet traffic monitoring and traffic characterization are essential for managing and optimizing network infrastructures. In general, the traffic classifier based on Machine Learning (ML) might not perform well for some cases such as imbalanced data sets. To address this issue, we propose an evaluation measure aiming for the case of imbalance multi-class network traffic classification based on the...
Network traffic demand is increasing explosively because of various smart equipment and services on smart era. It causes traffic overload for wireless and wired network. Network management system is very important to control the explosion of data traffic. It uses SNMP to communicate with various network resources for management functions, and creates lots of network management traffic. Those are can...
Internet flows characteristics are important reference for network behaviors research. However, there are few latest related studies and comparative analysis on different networks is especially rare. Based on traffic traces from CAIDA and CERNET, this paper presents a detailed and comprehensive comparison on Internet flows characteristics, including the fine-grained distributions of lifetime, size,...
Network traffic monitoring and traffic characterization are essential for network management and optimization. Extensive researches have been conducted in the past to characterize the network traffic. However, due to the increasing number of ADSL and CDMA users and the rapid development of new services in China, the results are out-of-dated and a deep understanding of the traffic pattern in both networks...
Recently, the number of Internet applications available for use on both desktop computers and smartphones has rapidly increased. The Internet traffic generated by these applications has increased significantly as well. Network operators are required to be aware of the status of managed networks in terms of application usage. However, the application traffic observed in a network is dependent on users...
The popularization of network P2P applications has brought a significant influence on people's Internet utilization behavior. In this context, this research conducted the case study at a university in Jiangsu province by analyzing the large quantity of data collected from high-performance network traffic control equipments, in order to reveal the distribution characteristics, changing pattern, and...
A surge of applications of p2p technology brings in problems such as the bandwidth shortage, internet piracy, and network security and so on. Accurate Identification of P2P traffic grows more important in effective network management. In this paper, a new P2P identification method based on compound characteristics is proposed. The accuracy of traditional identification methods will vary with different...
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