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Systems and methods for anomaly detection in automated workflow event decisions in a machine learning-based digital threat mitigation platform
Systems and methods for anomaly detection in automated workflow event decisions in a machine learning-based digital threat mitigation platform
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机译:基于机器学习的数字威胁缓解平台中自动工作流程事件决策中的异常检测的系统和方法
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摘要
A system and method for automated anomaly detection in automated disposal decisions of an automated decisioning workflow includes collecting a time-series of automated disposal decision data for a current period from an automated decisioning workflow, wherein the automated decisioning workflow computes one of a plurality of distinct disposal decisions for each distinct input comprising subject online event data and a machine learning-based threat score computed for the subject online event data; selecting an anomaly detection algorithm from a plurality of distinct anomaly detection algorithms based on a type of online abuse or online fraud that the automated decisioning workflow is configured to evaluate; evaluating, using the selected anomaly detection algorithm, the time-series of automated decision data for the current period; computing whether anomalies exist in the time-series of automated disposal decision data for the current period based on the evaluation; and generating an anomaly alert based on the computation.
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