Method for detecting network attack behaviors

A network attack and behavior technology, applied in the theoretical fields of network information security and mathematical statistics, can solve the problems of difficult to find system information, large amount of data, weak reliability, etc. The effect of low detection rate

Inactive Publication Date: 2010-06-23
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

Its method directly conducts statistical analysis on the entire flow data, the amount of data is large, and it is difficult to find the information in the system. Secondly, it relies on a single slow variable sequence for detection, which has weak reliability and high false detection rate.

Method used

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  • Method for detecting network attack behaviors
  • Method for detecting network attack behaviors
  • Method for detecting network attack behaviors

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Embodiment Construction

[0015] Below in conjunction with accompanying drawing and example the present invention is described in further detail:

[0016] (1) Phase space reconstruction of network traffic time series, and establish a statistical distribution model based on normal network traffic time series.

[0017] (1.1) According to the complex nonlinear characteristics of network traffic time series, the method of phase space reconstruction is selected, and the network traffic time series is reconstructed into multi-dimensional phase space. It has been proved that when the embedding dimension m and the time delay τ are determined, the reconstructed phase space can have the same geometric and information properties as the actual dynamical system, and have all the characteristics of the real space. Therefore, we use the method of phase space to study and analyze abnormal network traffic. After reconstruction, the phase space can maintain the invariance of the internal structure of the original networ...

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Abstract

The invention discloses a method for detecting network attack behaviors, which comprises the following steps: (1) reconstructing a network traffic time sequence to be detected to a multi-dimensional phase space according to the complicated non-linear property of network traffic, and establishing a statistic distribution module according to a normal network traffic time sequence; (2) carrying out smoothing treatment on the network traffic time sequence to be detected, and dividing into sub-windows; and (3) obtaining a parameter sequence according to parameters of all the sub-windows of the network traffic time sequence after the smoothing treatment according to the calculation of the statistic distribution module, and establishing a comprehensive decision module according to the parameter sequence for detecting abnormality. The network traffic is re-constructed to the multi-dimensional space, thereby fully displaying information hidden in a one-dimensional space, reducing the computational complexity of each dimensional space and improving the running speed; and the method can improve the robustness and the accuracy of a system and is characterized by low computational complexity, high detection rate and low false detection rate.

Description

technical field [0001] The present invention relates to related theories of network information security and mathematical statistics, and more specifically, relates to a method for detecting network attack behaviors. The method detects network attack behaviors based on phase space and hyperstatistical theory, and can detect network faults and performance problems in time , which is of great significance to improving the availability and reliability of the network and ensuring the quality of network service. Background technique [0002] Existing studies have shown that various network traffic flows have chaotic dynamic characteristics. Phase space reconstruction is an important method to study and analyze chaotic dynamical systems. The sequence of network traffic (abnormal network traffic) containing attack behavior is often a comprehensive reflection of the interaction of many system factors, which contains traces of all variables involved in the movement, rather than the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/26H04L12/56H04L29/06
Inventor 胡汉平杨越熊伟丁帆
Owner HUAZHONG UNIV OF SCI & TECH
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