Abstract
AbstractSecurity in telemedicine systems might be considered a particularly sensitive subject due to the type of confidential information generally handled and the responsibilities consequently derived. In this work we focus on detecting attempts of gaining unauthorised access to a telemedicine web application. We introduce a new Text Mining module that by using Text Categorisation of the web application server log entries is capable of learning the characteristics of both normal and malicious user behaviour. As a result, the detection of misuse in the web application is achieved without the need of explicit programming hence improving the system maintainability.KeywordsWeb Intrusion DetectionMachine LearningText MiningTelemedicine
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