MARKOV MODEL: Analyzing its behavior for Uncertainty conditions

Abstract

Markov model is used to analyze the dynamic behavior of the system in predicting the next state with the previous state. The process of attempting to guess the next character reveals information about the password strategy. In this paper, we give fuzzy inferences about the guessing passwords, by examining with the previous state and computing the possible outcomes of probability of each character. For some problems there cannot be complete solutions. For such problems Fuzzy inferences allow us to evaluate sub expressions. In the present paper, we discuss how to trace out some uncertainty conditions and analyze their behavior using fuzzy inference system and finally test the system for finding steady state behavior in guessing the characters in the password.

Keywords: Markov model, Fuzzy sets, Transition matrix, Membership functions, Fuzzy Logic