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Intrusion detection in web applications using text mining

机译:使用文本挖掘的Web应用程序中的入侵检测

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摘要

Information security has evolved from just focusing on the network and server layers to also include the web application layer. In fact, security in some types of web applications is often considered a particularly sensitive subject. Achieving a secure web application involves several different issues like encrypting traffic and certain database information, strictly restricting the access control, etc. In this work we focus on detecting attempts of either gaining unauthorised access or misusing a web application. We introduce an intrusion detection software component based on text-mining techniques. By using text categorisation, it is capable of learning the characteristics of both normal and malicious user behaviour from the log entries generated by the web application server. Therefore, the detection of misuse in the web application is achieved without the need of any explicit programming or code writing, hence improving the system maintainability. Because telemedicine systems are usually critical in terms of the confidential information handled and the responsibilities consequently derived, we apply and evaluate our methods on a real web-based telemedicine system called Arnasa.
机译:信息安全已经从仅关注网络和服务器层发展到也包括Web应用程序层。实际上,某些类型的Web应用程序中的安全性通常被认为是特别敏感的主题。实现安全的Web应用程序涉及几个不同的问题,例如对流量和某些数据库信息进行加密,严格限制访问控制等。在这项工作中,我们着重于检测试图获得未经授权的访问或滥用Web应用程序的企图。我们介绍一种基于文本挖掘技术的入侵检测软件组件。通过使用文本分类,它能够从Web应用程序服务器生成的日志条目中了解正常和恶意用户行为的特征。因此,不需要任何明确的编程或代码编写就可以检测Web应用程序中的滥用情况,从而提高了系统的可维护性。由于远程医疗系统通常对于处理机密信息和由此产生的责任至关重要,因此我们在称为Arnasa的基于网络的真实远程医疗系统上应用和评估我们的方法。

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