ATMSim: An anomaly teletraffic detection measurement analysis simulator

作者：Lee Jong Suk R; Ye Sang Kug; Jeong Hae Duck J^*

来源：Simulation Modelling Practice and Theory, 2014, 49: 98-109.

DOI：10.1016/j.simpat.2014.09.001

• Anomaly teletraffic detection
• Simulator
• Stochastic self-similarity
• Hurst parameter
• Hadoop

Over the last few years, the quantity of teletraffic is rapidly growing because of the explosive increase of Internet users and its applications. The needs of collection, storage, management, analysis, and measurement of the subsequent teletraffic have emerged as some of the very important issues. To this point many studies for detecting anomaly teletraffic have been done. Detection, measurement, and analysis studies for traffic data, however, are not actively being made based on Hadoop. In this paper, some problems and solutions for those systems have been suggested. We have also designed and developed an Anomaly Teletraffic detection Measurement analysis Simulator, called the ATMSim. One strong point of the ATMSim is able to store, measure, and analyze traffic data for detecting anomaly teletraffic. The other strength is to generate sequences of input synthetic anomaly teletraffic with various network attacks for practical network security applications. All simulations were executed under the control of the ATMSim simulator to investigate how input anomaly teletraffic with network attacks can be different from real Ethernet local area network (LAN) traffic. Our numerical results show that the values of the estimated Hurst parameter obtained from the anomaly teletraffic are much higher when compared to real Ethernet LAN traffic.

• 出版日期2014-12