Automated anomaly detection service on heterogeneous log streams

Systems and methods are disclosed for handling log data from one or more applications, sensors or instruments by receiving heterogeneous logs from arbitrary/unknown systems or applications; generating regular expression patterns from the heterogeneous log sources using machine learning and extractin...

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Bibliographic Details
Main Authors Zhang Hui, Jiang Guofei, Arora Nipun, Xu Jianwu, Debnath Biplob
Format Patent
LanguageEnglish
Published 27.03.2018
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Systems and methods are disclosed for handling log data from one or more applications, sensors or instruments by receiving heterogeneous logs from arbitrary/unknown systems or applications; generating regular expression patterns from the heterogeneous log sources using machine learning and extracting a log pattern therefrom; generating models and profiles from training logs based on different conditions and updating a global model database storing all models generated over time; tokenizing raw log messages from one or more applications, sensors or instruments running a production system; transforming incoming tokenized streams are into data-objects for anomaly detection and forwarding of log messages to various anomaly detectors; and generating an anomaly alert from the one or more applications, sensors or instruments running a production system.
Bibliography:Application Number: US201615352546