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Document History System and its Application to Abnormal Document Access Pattern Detection with a Probabilistic Model

机译:文档历史系统及其在具有概率模型的异常文档访问模式检测中的应用

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We present a design and implementation of tracing document history and its application to detecting abnormal document access patterns. We have been working on Document History System, which enables us to trace complete access history of operations for both electronic and paper documents. Document History System organizes access pattern trees based on dependency of user operations on documents. We also present a new probabilistic model, Multilayered Tree Markov Model (MTMM), in order to analyze access pattern trees of documents. The main feature of MTMM is to conduct tree pattern summarization and multilevel structural abstraction for trees. Our contribution is multi-level structural abstraction by incorporating hierarchical inner-state structure of Markov Model. Abnormal patterns, such as sending documents to unexpected users, can be detected by applying MTMM to access pattern trees of Document History System. We clarify the feasibility and effectiveness of our MTMM by several experiments for synthetic trees and real document access pattern trees.
机译:我们介绍了跟踪文档历史的设计和实现以及检测异常文档访问模式的应用。我们一直在研究文档历史系统,这使我们能够追踪电子和纸质文档的完整访问历史记录。文档历史系统根据用户操作对文档的依赖组织访问模式树。我们还提出了一种新的概率模型,多层树马尔可夫模型(MTMM),以分析文件的访问模式树。 MTMM的主要特点是为树进行树模式摘要和多级结构抽象。我们通过合并马尔可夫模型的分层内部结构,我们的贡献是多级结构抽象。可以通过应用MTMM来访问文档历史系统的模式树来检测异常模式,例如向意外用户发送文档。我们通过综合树木和真实文件访问模式树的几个实验阐明了MTMM的可行性和有效性。

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