Power grid security risk prediction method

A technology for risk prediction and power grid security, applied in electrical components, data exchange networks, instruments, etc., can solve problems such as low difficulty in use, inability to meet real-time requirements, and difficulty in parameter determination, reducing workload and alleviating poor prediction accuracy. High, alleviate the effect of too large

Active Publication Date: 2017-02-01
GLOBAL ENERGY INTERCONNECTION RES INST CO LTD +2
View PDF6 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The gray prediction method is difficult to use and has a good prediction effect on linear data, but the prediction accuracy is slightly insufficient and cannot reflect the actual situation of the network and other issues; the network security situation assessment method based on immune theory can only reflect the trend of security situation The real-time accuracy of network security situation prediction needs to be improved; the network security situation prediction method based on likelihood BP uses the situation evaluation model to establish a situation sequence as a training sequence, but the parameter training process of this method is complicated, the convergence speed is slow, and it cannot meet the real-time requirements ; The situation prediction method based on RBF neural network uses RBF neural network to process nonlinear situation values, and predicts the situation through the relationship between situation values. However, this method is prone to fall into local optimization problems in real-time network situation awareness, and may It leads to unstable results; the hidden Markov model is widely used in the field of network security, but this method has

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
  • Power grid security risk prediction method
  • Power grid security risk prediction method
  • Power grid security risk prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] In order to better understand the present invention, the content of the present invention will be further described below in conjunction with the accompanying drawings and examples.

[0043] The present invention provides a method for predicting power grid security risks, the method comprising the following steps:

[0044] Step 1, screen out the main network security situation factors and process them:

[0045] Obtain the historical log information of the equipment in the power network, and filter out the main network security situation factors that affect the network security situation through the analysis and calculation of the gray correlation degree, process the relevant historical data according to the selected network security situation factors, and perform dimensionless deal with.

[0046] In the step I, in the actual application of the Internet, the factor of the network security situation is the multi-source heterogeneous observation data obtained from the int...

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 relates to a power grid security risk prediction method. The method comprises steps that screened network security posture factors are processed; security posture state classification standards are determined; a hidden Markov model is constructed according to actual power grid conditions; hidden Markov model parameters are updated according to present security posture of equipment; security posture of an integral electric power network is calculated; a prediction risk value of the equipment and a weight prediction risk value are calculated. Through the method, the network security posture factors are deeply researched, the factors having greatest influence on the security posture are screened out, data processing workload is reduced, model training is carried out through utilizing the data relevant to the security posture factors, a problem of over-hugeness of a hidden Markov transition matrix is effectively alleviated, moreover, problems of non-high prediction precision and parameter determination difficulty are alleviated.

Description

technical field [0001] The invention relates to a safety risk prediction method, in particular to a power grid safety risk prediction method. Background technique [0002] At present, my country's information security construction is also advancing with the development of technology, but the number of people who are harmed by the Internet is also increasing year by year. From the perspective of the national information security situation, at present, the basic, overall and all-member role of the information system is increasing day by day. As an important guarantee for the in-depth promotion of informatization, information security has become an important part of the national security strategy. The state has successively promulgated the "2006-2020 National Informatization Development Strategy", "Notice on Strengthening Information Security Management of Industrial Control Systems" (2011); "(2012), the purpose is to enhance the security protection capabilities of important i...

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
IPC IPC(8): G06Q10/06G06Q50/06H04L12/24
CPCG06Q10/0635G06Q10/06375G06Q50/06H04L41/147
Inventor 李伟伟管小娟马媛媛邵志鹏石聪聪周诚李勇汪晨费稼轩
Owner GLOBAL ENERGY INTERCONNECTION RES INST CO LTD
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