一种面向工作流安全审计的扩展模型挖掘算法及应用

An extended mining algorithm for the security audit of workflow system and its application

工作流系统特有的内在领域知识和逻辑性使得简单应用现有的安全审计技术将会造成这些信息的丢失,从而降低安全监测的准确性和效率。另外,现有的工作流模型挖掘技术能较好地获取流程任务间的关系模型,有助于安全审计分析,但大多缺乏分析数据流与任务流的内在联系。因此,对工作流模型挖掘α算法引入了数据流的分析,使其在安全审计中有效地进行异常检测和入侵检测,从而提高了审计分析的准确性和有效性。

The domain knowledge and the inherent logic of workflow system make the simple application of existing security audit technology cause the above information missing, and therefore reduce the accuracy and efficiency of the security monitoring. The existing workflow model mining technology can be used to process the relationship model of tasks in the workflows, but most of them are lack of consideration about internal relations between data flow and task flow. Therefore, according to workflow model mining α-algorithm, data flow analysis was introduced. It can give the security audit a effective conduct of anomaly detection and intrusion detection, and thus can improve the accuracy of the audit analysis.