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Anomaly-based Intrusion Detection Systems (IDS) have the ability of detecting previously unknown attacks, which is important since new vulnerabilities and attacks are constantly appearing. Software as a service web applications are currently much targeted by attacks, so they are an obvious application for such IDSs. The paper presents a study of the use of anomaly-based IDSs with data from a production environment hosting a web application of large dimensions. It describes how challenges like processing a large number of requests and obtaining training data without attacks were solved. It also presents an evaluation comparing the accuracy obtained with the different types of models that were used to represent normal behavior.
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