Minería de datos aplicada en detección de intrusos
Based on the fundamentals and techniques of data mining can design and develop models to find illegal behavior easy to detect with the naked eye as it is not obvious information-priori unknown and potentially useful, in reference to particular facts. In particular, the usefulness of data mining in t...
| Autor Principal: | Vallejo P., Diego |
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| Otros Autores: | Tenelanda V, Germán |
| Formato: | info:eu-repo/semantics/article |
| Idioma: | spa |
| Publicado: |
Ingenierias
2018
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| Materias: | |
| Acceso en línea: |
2027-5846 |
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| Sumario: |
Based on the fundamentals and techniques of data mining can design and develop models to find illegal behavior easy to detect with the naked eye as it is not obvious information-priori unknown and potentially useful, in reference to particular facts. In particular, the usefulness of data mining in this area lies in a range of techniques, algorithms and methods that mimic the human characteristic of learning: ability to extract new knowledge from experience. Data mining has features such as analysis of large volumes of information, generation of behaviors that are not easily discernible, treatment of data for decision making. These features can be of vital importance to be applied in information security through intrusion detection. At present the information security is one of the great challenges facing the world, and especially the detection of anomalies in the access logs of different information systems. With this basic method applied is very efficient and able to prevent intrusions. It focuses in the field of intrusion detection to nurture the process of monitoring the events occurring in the network, followed by analysis of the same, with a view to identifying the factors that threaten the confidentiality, integrity, availability and non-repudiation of data. In the present work aims to show the contribution to the information security of data mining in the context of intrusion detection. |
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