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Traffic analysis and traffic abnormality detection are emerged as an efficient way of detecting network attacks in recent years. The existing approaches can be improved by introducing a new model

Traffic analysis and traffic abnormality detection are emerged as an efficient way of detecting network attacks in recent years. The existing approaches can be improved by introducing a new model and a new analysis method of network user’s traffic behaviors. The description dimensions to network user’s traffic behaviors in the current approaches are high, resulting in high processing complexity, high delay in differentiating an individual user’s abnormal traffic behavior from massive network data, and low detection rate.

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  • 2015-01-01
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    • NOTICE: this is the author's version of a work that was accepted for publication in SIMULATION MODELLING PRACTICE AND THEORY. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in SIMULATION MODELLING PRACTICE AND THEORY, 50, 176-188. DOI: 10.1016/j.simpat.2014.02.002, opens in a new window

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    Lai, Yingxu, Chen, Yinong, Liu, Zenghui, Yang, Zhen, & Li, Xiulong (2015). On monitoring and predicting mobile network traffic abnormality. SIMULATION MODELLING PRACTICE AND THEORY, 50, 176-188. http://dx.doi.org/10.1016/j.simpat.2014.02.002

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