Matlab application for information security risk analysis

Abstract

The problem of studying complex systems and processes using simulation in the MATLAB software package in the learning process is considered. There are general recommendations on effective configuration, selection of optimal parameters for the model being developed and practical use of the MATLAB software package functionality in educational programs of specialties and training areas, where the study of disciplines related to model development and various types of complex systems modeling is provided. There is noted the importance of modeling in the process of engineering education, when students learn to develop components of automated systems and evaluate their effectiveness. The object of the study is selected as automated systems that carry out remote monitoring of human health. The information security risk analysis in such systems is chosen as the modeling purpose. The features of the information security risk analysis process are described, its main stages and the preparation of initial data for modeling are presented. There are the implementation of the fuzzy logic and the fuzzy set theory in the Fuzzy Logic Toolbox package of the MATLAB software environment. The process of developing a fuzzy inference system, selecting the type of a fuzzy model, and setting its parameters are described in detail. The necessity of choosing the methods of logical conjunction and logical disjunction, aggregation, defuzzification, construction of membership functions, formation of fuzzy inference rules IF THEN is noted. The features of the conversion of a fuzzy model into a neuro-fuzzy network, as well as the formation of training, test and demonstration data for a neuro-fuzzy network are considered. An example of the development and configuration of a neuro-fuzzy network for information security risk analysis in automated systems for remote health monitoring is given.