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Deep learning-based network intrusion detection and vulnerability scanning method and devices

A technology of network intrusion detection and deep learning, applied to electrical components, transmission systems, etc., to achieve the effects of enhanced defense capabilities, improved test efficiency, and high detection rates

Active Publication Date: 2018-07-31
JINING POWER SUPPLY CO OF STATE GRID SHANDONG ELECTRIC POWER CO +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] Aiming at the deficiencies in the existing technology, solve how to realize the real-time detection, data flow audit and vulnerability scanning of the power system network through the artificial intelligence technology based on deep learning and big data mining technology in the existing technology, so as to improve the operation stability of the power grid information system, To enhance the defense capability against network attacks, the present invention proposes a method and device for network intrusion detection and vulnerability scanning based on deep learning

Method used

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  • Deep learning-based network intrusion detection and vulnerability scanning method and devices
  • Deep learning-based network intrusion detection and vulnerability scanning method and devices
  • Deep learning-based network intrusion detection and vulnerability scanning method and devices

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0065] The purpose of Embodiment 1 is to provide a network intrusion detection and vulnerability scanning method based on deep learning.

[0066] In order to achieve the above object, the present invention adopts the following technical scheme:

[0067] Such as figure 1 as shown,

[0068] A network intrusion detection and vulnerability scanning method based on deep learning, the method comprising:

[0069] Step (1): collecting malicious sample files and establishing a malicious file database;

[0070] Step (2): Use the deep learning algorithm to carry out training modeling according to the behavior of malicious files in the malicious file database, and carry out real-time monitoring model incremental training according to the received new malicious sample files to obtain the classification model;

[0071] Step (3): simulate the malicious sample files in the malicious file database in different environments, and use IDS to detect the attack characteristics of the malicious s...

Embodiment 2

[0114] The purpose of Embodiment 2 is to provide a computer-readable storage medium.

[0115] In order to achieve the above object, the present invention adopts the following technical scheme:

[0116] A computer-readable storage medium, in which a plurality of instructions are stored, and the instructions are adapted to be loaded by a processor of a terminal device and perform the following processing:

[0117] Step (1): collecting malicious sample files and establishing a malicious file database;

[0118] Step (2): Use the deep learning algorithm to carry out training modeling according to the behavior of malicious files in the malicious file database, and carry out real-time monitoring model incremental training according to the received new malicious sample files to obtain the classification model;

[0119] Step (3): simulate the malicious sample files in the malicious file database in different environments, and use IDS to detect the attack characteristics of the malicio...

Embodiment 3

[0122] The purpose of Embodiment 3 is to provide a terminal device.

[0123] In order to achieve the above object, the present invention adopts the following technical scheme:

[0124] A terminal device, including a processor and a computer-readable storage medium, the processor is used to implement instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and performing the following processing:

[0125] Step (1): collecting malicious sample files and establishing a malicious file database;

[0126] Step (2): Use the deep learning algorithm to carry out training modeling according to the behavior of malicious files in the malicious file database, and carry out real-time monitoring model incremental training according to the received new malicious sample files to obtain the classification model;

[0127] Step (3): simulate the malicious sample files in the malicious file datab...

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PUM

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Abstract

The invention discloses a deep leaning-based network intrusion detection and vulnerability scanning method and devices. The method comprises the steps of collecting malicious sample files and buildinga malicious file database; performing training modeling according to behaviors of malicious files in the malicious file database by using a deep learning algorithm, performing real-time monitored model incremental training according to received new malicious sample files, so as to obtain classified models; simulating and running the malicious sample files in the malicious file database in different environments, and detecting an attack characteristic of the malicious sample files by using IDS; and analyzing the malicious file database by using a data mining algorithm, building a vulnerabilityattack manner characteristic library, generating a network attack package, and scanning network vulnerabilities.

Description

technical field [0001] The invention belongs to the technical field of network security, and in particular relates to a network intrusion detection and vulnerability scanning method and device based on deep learning. Background technique [0002] In recent years, the number and scale of network attacks have increased dramatically, and the intrusion detection and vulnerability scanning system has become a must-have system for enterprise network facilities. The information system of the State Grid Corporation of China is listed as a key information infrastructure and is regarded as an important strategic resource of the country. Protecting the security of key information infrastructure has become the core content of the current company's network security construction. However, the current intrusion detection system and vulnerability scanning system for ensuring network security have the following problems: [0003] (1) Rule-based intrusion detection system [0004] Existing ...

Claims

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Application Information

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IPC IPC(8): H04L29/06
CPCH04L63/1416H04L63/1433H04L63/1441
Inventor 袁宝高强马广鹏刘宗杰乔亚男李辉陈伦马志腾张翠珍冯庆云杨涛丛超张坤孙春刚李文旭张延霞张颜艳付正鑫刘秀秀吕德志
Owner JINING POWER SUPPLY CO OF STATE GRID SHANDONG ELECTRIC POWER CO
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