Multibyte heterogeneous log preprocessing

    公开(公告)号:US10474642B2

    公开(公告)日:2019-11-12

    申请号:US15659131

    申请日:2017-07-25

    Abstract: Methods and systems for log management include pre-processing heterogeneous logs and performing a log management action on the pre-processed plurality of heterogeneous logs. Pre-processing the logs includes performing a fixed tokenization of the heterogeneous logs based on a predefined set of symbols, performing a flexible tokenization of the heterogeneous logs based on a user-defined set of rules, converting timestamps in the heterogeneous logs to a single target timestamp format, and performing structural log tokenization of the heterogeneous logs based on user-defined structural information.

    Automated event ID field analysis on heterogeneous logs

    公开(公告)号:US10237295B2

    公开(公告)日:2019-03-19

    申请号:US15429849

    申请日:2017-02-10

    Abstract: A system, program, and method for anomaly detection in heterogeneous logs. The system having a processor configured to identify pattern fields comprised of a plurality of event identifiers. The processor is further configured to generate an automata model by profiling event behaviors of the plurality of event sequences, the plurality of event sequences grouped in the automata model by combinations of one or more pattern fields and one or more event identifiers from among the plurality of event identifiers, wherein for a given combination, the one or more event identifiers therein must be respectively comprised in a same one of the one or more pattern fields with which it is combined. The processor is additionally configured to detect an anomaly in one of the plurality of event sequences using the automata model. The processor is also configured to control an anomaly-initiating one of the network devices based on the anomaly.

    CONTENT-AWARE ANOMALY DETECTION AND DIAGNOSIS

    公开(公告)号:US20180131560A1

    公开(公告)日:2018-05-10

    申请号:US15793358

    申请日:2017-10-25

    Abstract: Methods and systems for detecting a system fault include determining a network of broken correlations for a current timestamp, relative to a predicted set of correlations, based on a current set of sensor data. The network of broken correlations for the current timestamp is compared to networks of broken correlations for previous timestamps to determine a fault propagation pattern. It is determined whether a fault has occurred based on the fault propagation pattern. A system management action is performed if a fault has occurred.

    Automated anomaly detection service on heterogeneous log streams

    公开(公告)号:US09928155B2

    公开(公告)日:2018-03-27

    申请号:US15352546

    申请日:2016-11-15

    CPC classification number: G06F11/3612 G06F11/0706 G06F11/0766 G06F11/3636

    Abstract: 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.

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