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Classifying user behavior as abnormal

机译:将用户行为归类为异常

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying user behavior as anomalous. One of the methods includes obtaining user behavior data representing behavior of a user in a subject system. An initial model is generated from training data, the initial model having first characteristic features of the training data. A resampling model is generated from the training data and from multiple instances of the first representation for a test time period. A difference between the initial model and the resampling model is computed. The user behavior in the test time period is classified as anomalous based on the difference between the initial model and the resampling model.
机译:用于将用户行为分类为异常的方法,系统和装置,包括在计算机存储介质上编码的计算机程序。该方法之一包括获得表示用户在主题系统中的行为的用户行为数据。从训练数据生成初始模型,该初始模型具有训练数据的第一特征。在训练时间段内,从训练数据和第一表示的多个实例中生成重采样模型。计算初始模型和重采样模型之间的差异。根据初始模型和重采样模型之间的差异,将测试时间段内的用户行为分类为异常。

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