Information System Based On Rough Set Data Analysis, Risk Assessment Decision Support System

Nowadays in the large scale network environment of open system interconnection,the risk of information system always exist.It's necessary to apply the effective risk management to avoid risk events.The risk analysis and evaluation of information system is the key step. This dessertation emphasis study on the application of rough sets theory to risk evaluation of information system.The knowledge discovery method based on rough sets can mine risk rules from historical risk evaluation data. These risk rules will be used to help experts to make decision.The main content and achievements will be introduced in detail in the following text:Firstly, this dessertation put forward an effective solution to the problem of rough sets theory:discretization of the continuous attributes.The solution is to combine cloud model with rough sets theory. Firstly we use cloud model to discretize continuous data, and then use knowledge discovery method based on rough sets to mine rules.And experiment shows that the combination of inductive learning approach based on rough sets theory and cloud model based discretization algorithm tend to generate simpler rules. Besides,the rules tend to have higher precision.Secondly,an attribute reduction algorithm based on improved genetic algorithm is brought forward.The improvement include two parts:using diploid chromosome who has one dominant chromosome and one recessive chromosom instead of haploid in initial population; the adaptive technique is introduced.It can adjust crossover probability and mutation probability dynamically in course of evolution according to the adaptive fitness of population. By computing example it has been proved more faster for the attribute reduction algorithm based on improved genetic algorithm to be used for searching the best reduction than the attribute reduction algorithm based on genetic algorithm.Finally,an rough sets data analyze based risk evaluation decision support system of information system is constructed.The system can mine risk rules from historical risk evaluation data.Then experts can use these risk rules to make decision.This chapter introduce the system architecture and function of submodules , and then present work flow of core module via simulative experiment.