Research on Network Attack and Defense of SCADA System Model Based on FNN
| Autor: | Cao Xiedong, Tao Yu, Chela Zhang, Zhidi Chen |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Artificial neural network
Computer science business.industry Knowledge engineering ComputerApplications_COMPUTERSINOTHERSYSTEMS Construct (python library) computer.software_genre Expression (mathematics) Qualitative reasoning SCADA State space Artificial intelligence Data mining business Equivalence partitioning computer |
| Zdroj: | 2013 International Conference on Computational and Information Sciences. |
| Popis: | In order to guarantee the safety operation of the SCADA system under network attack condition, it is important to construct an intelligent model on SCADA system including reasoning and judgment in network attack and defense. This paper describes the network attack knowledge based on the theory of the factor expression of knowledge, and studies the formal knowledge theory of SCADA network from the factor state space, equivalence partitioning, etc. It utilizes the factor neural network (FNN) theory which contains high-level knowledge and quantitative reasoning described to establish a predictive model including analytic FNN and analogous FNN. This model abstracts and builds an equivalent and corresponding network attack and defense knowledge factors system. Analysis shows that the network attack and defense strategy model of SCADA system according to the FNN has effective security defense performance in network attack, and it provides new methods of researching the security defense theory of SCADA system under the condition of network attack. |
| Databáze: | OpenAIRE |
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