Data Leakage Detection Using Dynamic Data Structure and Classification Techniques

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Auteur principal: César Byron Guevara Maldonado
Format: Artículo científico
Langue:en
Publié: Corporación Universitaria de la Costa 2015
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author César Byron Guevara Maldonado
author_facet César Byron Guevara Maldonado
contents Data Leakage Detection Using Dynamic Data Structure and Classification Techniques César Byron Guevara Maldonado Ingeniería UCS Naive Bayes Data Leakage Data Structure Decision Tree C4 Data leakage is a permanent problem in public and private institutions around the world; particularly, identifying the information leakage efficiently. In order to solve this problem, this paper poses an adaptable data structure based on human behavior using all the activities executed within the computer system. When applying this structure, the normal behavior is modeled for each user, so in this way, detects any abnormal behavior in real time. Moreover, this structure enables the application of several classification techniques such as decision trees (C4.5), UCS, and Naive Bayes, these techniques have proven efficient outcomes in intrusion detection. In the testing of this model, a scenario demonstrating the proposal’s effectiveness with real information from a government institution was designed so as to establish future lines of work. 2015 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779324008 en http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.1 Vol.11
format Artículo científico
id redalyc_497779324008
institution Redalyc
language en
publishDate 2015
publisher Corporación Universitaria de la Costa
spellingShingle Data Leakage Detection Using Dynamic Data Structure and Classification Techniques
César Byron Guevara Maldonado
Ingeniería
UCS
Naive Bayes
Data Leakage
Data Structure
Decision Tree C4
Data Leakage Detection Using Dynamic Data Structure and Classification Techniques César Byron Guevara Maldonado Ingeniería UCS Naive Bayes Data Leakage Data Structure Decision Tree C4 Data leakage is a permanent problem in public and private institutions around the world; particularly, identifying the information leakage efficiently. In order to solve this problem, this paper poses an adaptable data structure based on human behavior using all the activities executed within the computer system. When applying this structure, the normal behavior is modeled for each user, so in this way, detects any abnormal behavior in real time. Moreover, this structure enables the application of several classification techniques such as decision trees (C4.5), UCS, and Naive Bayes, these techniques have proven efficient outcomes in intrusion detection. In the testing of this model, a scenario demonstrating the proposal’s effectiveness with real information from a government institution was designed so as to establish future lines of work. 2015 artículo científico 0122-6517 https://www.redalyc.org/articulo.oa?id=497779324008 en http://www.redalyc.org/revista.oa?id=4977 INGE CUC application/pdf Corporación Universitaria de la Costa INGE CUC (Colombia) Num.1 Vol.11
title Data Leakage Detection Using Dynamic Data Structure and Classification Techniques
topic Ingeniería
UCS
Naive Bayes
Data Leakage
Data Structure
Decision Tree C4
url https://www.redalyc.org/articulo.oa?id=497779324008