scholarly journals Evaluating the Effectiveness of an Intrusion Detection System Based on Matrix Games and Fuzzy Sets

2021 ◽  
Vol 2096 (1) ◽  
pp. 012007
Author(s):  
V B Vilkov ◽  
A I Dergachev ◽  
A K Chernykh ◽  
M S Abu-Khasan

Abstract We consider a problem formulated as a matrix game in which the gain of officials using a specific intrusion detection system (criminal actions) of intruders (player 1) is the probability of timely detection of these criminal actions (player 2). As a rule, it is not possible to unambiguously set the probability of timely detection of criminal actions, so it is proposed to use the apparatus of fuzzy set theory to evaluate it. Reviewed and discussed the basic concepts of fuzzy set theory, and an example of practical application of this theory to assess the efficiency of the detection system of criminal damage. Application of fuzzy set theory in assessing the possible actions of an attacker can detect existing vulnerabilities in information security of automated systems continue to spend improving the detection of criminal acts (hackers) to prevent the possibility of applying economic and other damage to the company.

Author(s):  
Tarum Bhaskar ◽  
Narasimha Kamath B.

Intrusion detection system (IDS) is now becoming an integral part of the network security infrastructure. Data mining tools are widely used for developing an IDS. However, this requires an ability to find the mapping from the input space to the output space with the help of available data. Rough sets and neural networks are the best known data mining tools to analyze data and help solve this problem. This chapter proposes a novel hybrid method to integrate rough set theory, genetic algorithm (GA), and artificial neural network. Our method consists of two stages: First, rough set theory is applied to find the reduced dataset. Second, the results are used as inputs for the neural network, where a GA-based learning approach is used to train the intrusion detection system. The method is characterized not only by using attribute reduction as a pre-processing technique of an artificial neural network but also by an improved learning algorithm. The effectiveness of the proposed method is demonstrated on the KDD cup data.


Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 432 ◽  
Author(s):  
Vilém Novák

In this paper, we will visit Rough Set Theory and the Alternative Set Theory (AST) and elaborate a few selected concepts of them using the means of higher-order fuzzy logic (this is usually called Fuzzy Type Theory). We will show that the basic notions of rough set theory have already been included in AST. Using fuzzy type theory, we generalize basic concepts of rough set theory and the topological concepts of AST to become the concepts of the fuzzy set theory. We will give mostly syntactic proofs of the main properties and relations among all the considered concepts, thus showing that they are universally valid.


1990 ◽  
Vol 20 (1) ◽  
pp. 33-55 ◽  
Author(s):  
Jean Lemaire

AbstractFuzzy set theory is a recently developed field of mathematics, that introduces sets of objects whose boundaries are not sharply defined. Whereas in ordinary Boolean algebra an element is either contained or not contained in a given set, in fuzzy set theory the transition between membership and non-membership is gradual. The theory aims at modelizing situations described in vague or imprecise terms, or situations that are too complex or ill-defined to be analysed by conventional methods. This paper aims at presenting the basic concepts of the theory in an insurance framework. First the basic definitions of fuzzy logic are presented, and applied to provide a flexible definition of a “preferred policyholder” in life insurance. Next, fuzzy decision-making procedures are illustrated by a reinsurance application, and the theory of fuzzy numbers is extended to define fuzzy insurance premiums.


2020 ◽  
Vol 41 (45) ◽  
pp. 129-144
Author(s):  
Olga V. ARINICHEVA ◽  
◽  
Natalia A. LEBEDEVA ◽  
Aleksei V. MALISHEVSKII ◽  
◽  
...  

The article contains mathematical models of a person’s socionics characteristics based on fuzzy set theory. The practical application of the proposed models is focused on assessing professional aptitude of operators who have to process massive flows of information at a forced pace (for example, aircraft pilots or air traffic controllers).


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