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The current development of technologies has boosted the use of telecommunication services. This fact brings an increase in the volumes of data generated in telecommunication companies. Such data need to be processed in order to detect potential intruders or fraud. The rule evaluation techniques are widely used in these application contexts due to their high effectiveness over known attacks. The incorporation of an automatic rule generator allows it to obtain rules in large volumes of data, for assisting information analysts; thus, the accuracy of intrusion detection is increased. In this paper, an automatic rule generation method is presented, including a strategy based on processing the patterns extracted from a training set and building classification rules. Finally, our proposal is evaluated and compared regarding other classifiers, achieving good results.Keywords: Automatic rule generation, frequent subgraph mining, intrusion detection. RESUMEN El desarrollo actual de las tecnologías ha impulsado el uso de servicios de telecomunicaciones. Este hecho implica un aumento en los volúmenes de datos generados en las empresas de telecomunicaciones. Dichos datos requieren ser procesados con el fin de detectar potenciales intrusos o fraudes. Las técnicas de evaluación regla son ampliamente utilizadas en estos contextos de aplicación por su alta efectividad sobre ataques conocidos. La incorporación de un generador automático de reglas en dichas técnicas

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