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Flow analysis method based on ARMA (Autoregressive Moving Average) model and chaotic time sequence model

A technology for chaotic time series and traffic analysis, applied in digital transmission systems, electrical components, transmission systems, etc., can solve problems such as affecting normal business operation, normal business interruption, increasing network resource pressure, etc., to achieve good actual forecast application value, The effect of improving accuracy

Inactive Publication Date: 2012-04-04
JIANGSU XINWANG TEC TECH
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Problems solved by technology

The flooding of various abnormal traffic behaviors on the network backbone greatly increases the pressure on network resources, consumes too much network resources, and affects the normal business operation to a large extent
In severe cases, these abnormal network behaviors will cause network paralysis and interruption of normal business

Method used

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  • Flow analysis method based on ARMA (Autoregressive Moving Average) model and chaotic time sequence model
  • Flow analysis method based on ARMA (Autoregressive Moving Average) model and chaotic time sequence model
  • Flow analysis method based on ARMA (Autoregressive Moving Average) model and chaotic time sequence model

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Embodiment Construction

[0019] The technical scheme of the present invention is described in detail below in conjunction with accompanying drawing:

[0020] as attached figure 1 As shown, the inventive method carries out flow control and abnormal flow monitoring according to the following steps:

[0021] Step 1: Monitor the traffic in the network, intercept the original data packet by the network device driver, perform traffic statistics, and write to the database and log files.

[0022] The collection of network traffic must bypass the protocol stack of the operating system to access the original data packets transmitted on the network, which requires a part to run inside the core of the operating system and directly interact with the network interface driver. This method uses two different libraries of Winpcap: packet.dll and wpcap.dll. The former provides a low-level API, accompanied by a programming interface independent of the Microsoft operating system, and these APIs can be directly used to ...

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Abstract

The invention discloses a flow analysis method based on an ARMA (Autoregressive Moving Average) model and a chaotic time sequence model. By adopting the flow analysis method, the flow gathering, the feature extraction, the flow analysis, the flow forecasting and the abnormal flow detection can be realized. The flow analysis method comprises the following steps of firstly, monitoring and counting flow by calculating Hurst indexes, ARMA parameters, fractional difference, relevant dimension and time delay and estimating Lyapunov indexes; carrying out certain step-length forecasting on a sample point according to the parameters and the forecasting formula which are provided by the flow analysis; and early warning the abnormal flow in a network according to the variation of the Hurst indexes.

Description

technical field [0001] The invention relates to network flow control and abnormal flow monitoring, in particular to a flow analysis method based on an ARMA model and a chaotic time series model, belonging to the technical field of network flow control. Background technique [0002] How to improve the availability of large-scale backbone networks and maximize the controllability and effectiveness of the backbone network has become the focus and difficulty of network security construction for government agencies, enterprises, service providers, and data centers. The flooding of various abnormal traffic behaviors on the network backbone greatly increases the pressure on network resources, consumes too much network resources, and affects the normal business operation to a large extent. In severe cases, these abnormal network behaviors will cause network paralysis and interruption of normal business. Therefore, new requirements for monitoring and analysis are put forward for the...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/26H04L12/56H04L12/801
Inventor 孙建张梅琴张顺颐王攀
Owner JIANGSU XINWANG TEC TECH
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