Interactive visualization of a relationship of isolated execution environments

    公开(公告)号:US12254019B2

    公开(公告)日:2025-03-18

    申请号:US18160972

    申请日:2023-01-27

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described to determine relationships between one or more components of an isolated execution environment system based on data obtained from a data intake and query system. Based on the determined relationships, an interactive visualization is generated that indicates the hierarchical relationship of the components. In some cases, to illustrate the relationship between components of the isolated execution environment system, the visualization can include one or more display objects displayed in a subordinate or superior relationship to other display objects. In certain cases, based on an interaction with a display object, the system can generate a query and/or display additional information and/or visualizations based on the results of the query.

    Implementation of a data processing pipeline using assignable resources and pre-configured resources

    公开(公告)号:US12242892B1

    公开(公告)日:2025-03-04

    申请号:US17444157

    申请日:2021-07-30

    Applicant: Splunk Inc.

    Inventor: Ricky Burnett

    Abstract: Systems and methods are described for a implementing a streaming data processing system that includes a pool of pre-configured resources and a pool of dedicated resources. The streaming data processing system can implement a processing pipeline using compute resources. The pool of pre-configured resources can support previews of processing pipelines for a plurality of users and the pool of dedicated resources can support full deployments of processing pipelines for a particular user. The streaming data processing system can implement a preview of a processing pipeline using a pre-configured resource of the pool of pre-configured resources. Further, the streaming data processing system can implement the processing pipeline using a dedicated resource of the pool of dedicated resources. The streaming data processing system can provision the dedicated resource and deploy the processing pipeline using the dedicated resource.

    Anomaly Detection System and Method for Implementing a Data Regularity Check and Adaptive Thresholding

    公开(公告)号:US20250028618A1

    公开(公告)日:2025-01-23

    申请号:US18222870

    申请日:2023-07-17

    Applicant: Splunk Inc.

    Abstract: Computerized methodologies are disclosed that are directed to detecting anomalies within a time-series data set. A first aspect of the anomaly detection process includes analyzing the regularity of the data points of the time-series data set and determining whether a data aggregation process is to be performed based on the regularity of the data points, which results in a time-series data set having data points occurring at regular intervals. A seasonality pattern may be determined for the time-series data set, where a silhouette score is computed to measure the quality of the fit of the seasonality pattern to the time-series data. The silhouette score may be compared to a threshold and based on the comparison, the seasonality pattern or a set of heuristics may be utilized in an anomaly detection process. When the seasonality pattern is utilized, the seasonality pattern may be utilized to generate thresholds indicating anomalous behavior.

    Graph-based detection of network security issues

    公开(公告)号:US12206693B1

    公开(公告)日:2025-01-21

    申请号:US17745482

    申请日:2022-05-16

    Applicant: Splunk Inc.

    Abstract: The disclosed techniques relate to a graph-based network security analytic framework to combine multiple sources of information and security knowledge in order to detect risky behaviors and potential threats. In some examples, the input can be anomaly events or simply regular events. The entities associated with the activities can be grouped into smaller time units, e.g., per day. The riskiest days of activity can be found by computing a risk score for each day and according to the features in the day. A graph can be built with links between the time units. The links can also receive scoring based on a number of factors. The resulting graph can be compared with known security knowledge for adjustments. Threats can be detected based on the adjusted risk score for a component (i.e., a group of linked entities) as well as a number of other factors.

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