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    An Intrusion Detection System Using Apache Log Files
    (Ieee, 2019) Ince, Cemile; Omac, Zeki
    Today, thousands of systems are exposed to attacks every day. For this reason, many studies have been done in this area. These studies, using data mining (VM) and machine learning techniques, are trying to determine the intrusion detection by examining the log files in different OSI layers. These studies generally use standard data sets and propose hybrid systems to increase the success rate. In this study, an attack detection system (STS) has been developed by using Inonu University web page log files. The log files used as a data set consist of more than 35 million requests and a total of 326 attacks. As a result, the system was trained using artificial neural network (ANN) and attacks were detected with 99.3% success.