Docker-based automated honey pot construction and threat perception method

A honeypot and algorithm technology, applied in the field of visualization technology, can solve the problems of high resource occupation, high deployment cost of honeypot system, and inability to make full use of computer storage and computing resources, so as to achieve a high degree of automation, reduce economic losses, and ease operation burden effect

Active Publication Date: 2018-11-27
EAST CHINA NORMAL UNIVERSITY
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Problems solved by technology

[0004] In addition, most of the current honeypot systems are deployed on physical machines, which take up a lot of resources and cannot make full use of the limited storage

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  • Docker-based automated honey pot construction and threat perception method
  • Docker-based automated honey pot construction and threat perception method
  • Docker-based automated honey pot construction and threat perception method

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Embodiment Construction

[0030] The present invention will be further described in detail in conjunction with the following specific embodiments and accompanying drawings.

[0031] refer to figure 1 , the present invention provides a kind of method based on Docker automatic honeypot construction and threat awareness, comprising the following steps:

[0032] Step 1: Create and run the honeypot data collection container;

[0033] Step 2: Use data processing algorithms to format the original data;

[0034] Step 3: Perform deep model training on the formatted data;

[0035] Step 4: Use NodeJS as the Web background for data visualization;

[0036] Step 5: Use the deep model obtained in step 3 to discriminate the unknown traffic.

[0037] refer to figure 2 , when creating and running the data acquisition container step, the present invention first judges whether there is a Docker operating environment in the system to be deployed, if there is an operating environment, then starts to pull the Docker ho...

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Abstract

The invention discloses a Docker-based automated honey pot construction and threat perception method. The method comprises: step one, creating and running a data collection container; step two, carrying out formatting processing on original data according to a data processing algorithm; step three, carrying out depth model training on the formatted data; step four, carrying out data visualizationby using NodeJS as a web background; and step five, determining an unknown flow by using a threat perception technology. Therefore, functions of data collection, data processing, data visualization and the like can be completed automatically; and parameters for model training need to be adjusted manually, so that the model becomes stable and accurate.

Description

technical field [0001] The invention belongs to the field of network security, and relates to Docker container virtualization technology, honeypot data collection technology, deep learning algorithm, Python automatic processing technology and visualization technology. The present invention combines the above several technologies to realize the automatic collection, processing, model training and visualization of honeypot data, and greatly simplifies the data collection and processing process. Background technique [0002] In a complex network environment, the systems deployed by users are under malicious attacks from network hackers all the time. A large amount of malicious traffic occupies the total access volume of user systems. Malicious traffic itself is extremely harmful. A successful malicious attack Traffic can cause a lot of loss to the user system. Although in the current defense measures, a series of software such as firewalls do help users filter out malicious tr...

Claims

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Application Information

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IPC IPC(8): H04L29/06
CPCH04L63/1416H04L63/1491
Inventor 陈铭松谢永康田放张建宁胡铭
Owner EAST CHINA NORMAL UNIVERSITY
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