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Título : Preprocessing Information from a Data Network for the Detection of User Behavior Patterns
Autor : Hidalgo-Guijarro, Jairo
Yandún-Velasteguí, Marco
Bolaños-Tobar, Dennys
Borja-Galeas, Carlos
Guevara-Maldonado, César
Varela-Aldás, José
Castillo-Salazar, David
Arias-Flores, Hugo
Fierro-Saltos, Washington
Rivera, Richard
Fecha de publicación : 2020
Editorial : Advances in Intelligent Systems and Computing. Volume 1026, Pages 661 - 667. 2nd International Conference on Human Systems Engineering and Design: Future Trends and Applications, IHSED 2019. Munich. 16 September 2019 through 18 September 2019
Resumen : This study focuses on the preprocessing of information for the selection of the most significant characteristics of a network traffic database, recovered from an Ecuadorian institution, using a method of classifying optimal entities and attributes, with the In order to achieve a complete understanding of its real composition to be able to generate patterns and identification of trends of behavior in the network, both of patterns that deviate from normal traffic behavior (intrusive), as well as normal, to detect with high precision possible attacks. Network management tools were used as a multifunctional security server software, as well as pre-processing of data tools for the selection of attributes, as well as the elimination of noise from the instances of the database, It allowed to identify which ins- tances and attributes are correct and contribute with effective information in the study. Among them we have: Greedy Stepwise Algorithm (Algoritmo Voráz), K-Means Algorithm, Discrete Chi-square Attributes and the use of computational models as Evolutionary Neural Networks and Gene Algorithms. © Springer Nature Switzerland AG 2020.
URI : https://link.springer.com/chapter/10.1007/978-3-030-27928-8_101
http://repositorio.uti.edu.ec//handle/123456789/3417
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