Intrusion detection method for fusion of multiple neutral networks

A technology of network fusion and intrusion detection, applied in the field of intrusion detection of multi-neural network fusion, can solve the problems of the intrusion detection system of the intelligent method of neural network, etc., and achieve the effect of good scalability and good compatibility

Inactive Publication Date: 2009-04-01
章毅 +1
View PDF0 Cites 52 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Therefore, a single neural network intelligence method is insufficient for building a complete intrusion detection system.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Intrusion detection method for fusion of multiple neutral networks
  • Intrusion detection method for fusion of multiple neutral networks
  • Intrusion detection method for fusion of multiple neutral networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] The present invention will be further described below with reference to the accompanying drawings and embodiments. like figure 1 As shown, the dotted line in the figure represents the offline data flow for training a neural network classifier or cluster analysis, while the solid line represents the online data processing flow.

[0036] Among them, the SGNG anomaly detection classifier uses the data collection of the closed network as training data to obtain the normal pattern of network data and behavior, and the training process is supervised training, which performs real-time detection on the open network data collected in real time; the purpose of the SGNG anomaly detection classifier It divides the input network connection data into two categories: normal data and abnormal data. refer to Figure 4 , SGNG anomaly detection classifier is a self-growing neural network model, and the traditional SOM self-organizing network mapping mechanism in different dimensional sp...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for detecting intrusion by multiple neuronic network confusion, which comprises the following steps: data from external network is subject to packet sniffing and analyzing; the processed network data is simultaneously transmitted to an analytical database and a SGNG exception detection classifier, and the SGNG exception detection classifier is trained offline by normal categorical data acquired by a close network; the SGNG exception detection classifier identifies the detected exceptional data, carries out system alarm and stores the exceptional data into the analytical database; a data set which is identified as exception in the analytical database is provided for a PCSOM exception cluster analyzer for exceptional data cluster analysis; the exceptional data detected by the SGNG exception detection classifier is input to a plurality of parallel PCANN misuse detector respectively according to classifications; the PCANN misuse detector carries out concrete intrusion classification alarm on the detected exceptional data, simultaneously, all the exceptional data filtered by the PCANN misuse detector is identified and stored in the analytical database.

Description

technical field [0001] The invention relates to the technical field of intrusion detection, in particular to a multi-neural network fusion intrusion detection method. Background technique [0002] In recent years, the frequent occurrence of network attacks and intrusions makes the research of intrusion detection system (IDS) technology more and more important. In the whole system security architecture, it plays a very important role for the system, the network and the user IDS. Generally speaking, a computer network system includes many security systems, such as network firewalls, vulnerability scanning systems, access control systems, and so on. But the intrusion detection system is the only system that can judge whether it is effective or not through the data and behavior patterns. For a successful intrusion detection system, it can not only make the system administrator aware of any changes in the network system (including programs, files and hardware devices), but also...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04L9/36
Inventor 章毅刘贵松蒲晓蓉屈鸿张蕾彭德中
Owner 章毅
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products