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| Formato: | Artículo científico |
| Lenguaje: | en |
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Corporación Universitaria de la Costa
2015
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| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=497779324008 |
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- 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