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Analysis and Comparison of Process Mining Algorithms with Application of Process Mining in Intrusion Detection System

机译：进程挖掘算法的分析与比较—进程挖掘在入侵检测系统中的应用

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Process mining assumes to find, screen and improve the genuine procedures through picking up understanding from the log events which are promptly accessible in the existing data framework. It gives the missing connection between one hand process, demonstrate examination and information arranged, investigation and then again execution and conformance. In this manuscript, we have discussed the process mining and intrusion detection concepts and compared the various algorithms which have been used in process mining. We have also discussed the application of process mining approach to detect the intrusions. Traditional information mining procedures, for example, characterization, grouping, relapse, affiliation administer learning, and arrangement/scene mining doesn't concentrate on the business process models and it is regularly used to advancement in the general procedure. Process mining centers around end-to-end forms and is conceivable in view of the developing accessibility of occasion information and developing the new processes and conformance checking with enhancement of the existing processes.
机译：流程挖掘假设通过从对日志事件的理解中找到，筛选和改进真正的过程，这些日志事件可以在现有数据框架中快速访问。它一方面提供了过程之间缺少的联系，另一方面展示了检查和信息整理，调查，然后再次执行和一致性。在本文中，我们讨论了过程挖掘和入侵检测的概念，并比较了过程挖掘中使用的各种算法。我们还讨论了过程挖掘方法在检测入侵方面的应用。传统的信息挖掘程序（例如，特征化，分组，复发，从属关系管理学习和安排/场景挖掘）并不专注于业务流程模型，而是定期用于一般过程的改进。流程挖掘以端到端的形式为中心，并且考虑到场合信息的可访问性不断发展以及开发新流程以及通过增强现有流程来进行一致性检查，这是可以想到的。

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