Information safety discrimination method and system based on learning diagnostor and related device

A technology of information security and discrimination method, applied in the field of information security, can solve the problems of lack, inability to use discrete event system state opacity discrimination method, inability to determine and so on

Active Publication Date: 2018-11-30
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The existing analysis of state opacity is based on a complete discrete event system (there is no lack of necessary state information). If a complete discrete event system is judged to have state opacity, it can be considered to meet the information confidentiality requirements ( That is, some information that does not want to be snooped by others has been successfully hidden), but it is often impossible to determine whether a discrete event system is complete when it is obtained, and once the discrete event system is incomplete, it cannot be used to apply to complete discrete event systems. The state opacity judgment method of the system, if the same judgment method is used forcibly, the judgment result obtained has no reference value, and the existing technology lacks consideration of such situations

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  • Information safety discrimination method and system based on learning diagnostor and related device
  • Information safety discrimination method and system based on learning diagnostor and related device
  • Information safety discrimination method and system based on learning diagnostor and related device

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Experimental program
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Embodiment 1

[0067] The following combination figure 1 , figure 1 A flow chart of an information security discrimination method based on a learning diagnostic device provided in an embodiment of the present application, which specifically includes the following steps:

[0068] S101: Generate an incomplete model according to the incomplete discrete event system;

[0069] In this step, firstly, the incomplete discrete event system is constructed as an incomplete model by using the finite state automata (equal to the process of the discrete event system G constructed above), and the incomplete discrete event system contains the state that needs to be kept secret Information, that is to say, this part of the status information that needs to be kept secret needs to be prevented from being snooped by others.

[0070] S102: Process the incomplete model by using the learning diagnostic device and the candidate state algorithm to obtain missing information of the complete model;

[0071] On the ...

Embodiment 2

[0086] The following combination figure 2 , figure 2 It is a flow chart of another information security discrimination method based on a learning diagnostic device provided by the embodiment of this application. On the basis of the first embodiment, this embodiment provides a method of how to specifically use a learning diagnostic device and a state candidate The algorithm obtains the method of partial state information missing in the incomplete model, and the specific implementation method is as follows:

[0087] S201: Generate an incomplete model according to the incomplete discrete event system;

[0088] S202: Construct a learning diagnostic device according to the state information output by the incomplete model;

[0089] S203: Use the candidate state algorithm to update information in each diagnosis cycle of the learning diagnostic device to obtain missing information of the complete model;

[0090] Firstly, a diagnostic device is constructed based on the state infor...

Embodiment 3

[0097] This embodiment proposes a method for judging the opacity of the current state of the system under the condition of an incomplete discrete event system. The method uses an automaton as G=(X, Σ, δ, x 0 , Y, λ) as the model, which is completed in four steps: first, according to the real model G t , resulting in an incomplete model G with missing states n In the hypothetical transition with the opacity of the current state; then divide the hypothetical transition, residual, and increase the residual operation to obtain the generator set Again for the incomplete model G n , by introducing a candidate c and a learned diagnostic LD of the learning function, the generator set is obtained Final comparison generator sets with builder set Judging that the system G has current state opacity, the specific method is as follows:

[0098] 1. According to the real model G t , resulting in an incomplete model G with missing states n In a hypothetical transition with current s...

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Abstract

The application discloses an information safety discrimination method based on a learning diagnostor, which is applied to an incomplete DES (Discrete Event System). An incomplete model is processed byintroducing the learning diagnostor with learning capacity and a candidate state algorithm, and by using a mode in the candidate state algorithm, which not only can carry out simulation on assumptivestate transfer, but also can recover missing state information of the system under a learning function of the learning diagnostor by keeping trying so as to convert the incomplete model into a complete model, the incomplete DES accords with the precondition of verifying opaqueness of a state so as to discriminate whether the incomplete DES successfully implements confidentiality on certain information and meanwhile, expand the application field of the learning diagnostor to the field of verifying opaqueness of the state. The application simultaneously further discloses an information safety discrimination system and device based on the learning diagnostor and a computer readable storage medium, which have the beneficial effects above.

Description

technical field [0001] The present application relates to the technical field of information security, in particular to an information security judgment method, system, device and computer-readable storage medium based on a learning diagnostic device. Background technique [0002] Discrete Event System (DES) is a kind of dynamic system that is caused by the interaction of discrete events according to certain operation rules and leads to state evolution. It can be directly used to model discrete systems and can be used to System modeling after system discretization. At present, discrete event systems have been successfully applied in military defense, traffic control, computer integrated manufacturing systems, electronic communication networks, robotics and other fields. [0003] With the increasing scale of industrial production, automation equipment is becoming larger and larger, and the system structure is becoming more and more complex. Once the industrial system is atta...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/45G06F21/60G06N99/00
CPCG06F21/45G06F21/60
Inventor 刘富春张旭赵锐
Owner GUANGDONG UNIV OF TECH
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