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1.
公开(公告)号:US20200344254A1
公开(公告)日:2020-10-29
申请号:US16872077
申请日:2020-05-11
Applicant: Splunk Inc.
Inventor: Kurt Kokko , Damien Lindauer , Brad Lovering , Lynn Kasel
Abstract: Techniques and mechanisms are disclosed for creating an environment for detecting malicious network traffic. A test computer network including a plurality of cloned nodes is created. The plurality of cloned nodes in the test computer network corresponds to at least some of a plurality of target nodes of a host computer network, and the test computer network has no network connectivity to the host computer network. Sensors in both the host computer network and the test computer network generate network flow records that are sent to a detection processing pipeline. The detection processing pipeline merges the records received from the sensors and uses the merged records to train at least one model used to identify instances of malicious network traffic.
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公开(公告)号:US11327992B1
公开(公告)日:2022-05-10
申请号:US16512899
申请日:2019-07-16
Applicant: Splunk Inc.
Inventor: Alexandros Batsakis , Clifton Gordon , Brad Lovering , Christopher Madden Pride
IPC: G06F16/00 , G06F16/25 , H04L29/06 , G06F16/903 , H04L67/60 , G06F16/901 , G06F9/50 , G06F16/908
Abstract: Systems and methods are disclosed for authenticating a user to use one or more components of a data intake and query system. The data intake and query system enables the generation or searching of events that include raw machine data associated with a timestamp. The data intake and query system receives a request for access via an application programming interface (API). Based on the request, the data intake and query system authenticates the user. The data intake and query system can receive a second request via the API for a component of the data intake and query system. Based on a determination that the user is authenticated, the data intake and query system can communicate the request to the component.
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3.
公开(公告)号:US20180219896A1
公开(公告)日:2018-08-02
申请号:US15885709
申请日:2018-01-31
Applicant: Splunk Inc.
Inventor: Kurt Kokko , Damien Lindauer , Brad Lovering , Lynn Kasel
CPC classification number: H04L63/1425 , G06F21/53 , G06F21/54 , G06N20/00 , H04L63/1433
Abstract: Techniques and mechanisms are disclosed for creating an environment for detecting malicious network traffic. A test computer network including a plurality of cloned nodes is created. The plurality of cloned nodes in the test computer network corresponds to at least some of a plurality of target nodes of a host computer network, and the test computer network has no network connectivity to the host computer network. Sensors in both the host computer network and the test computer network generate network flow records that are sent to a detection processing pipeline. The detection processing pipeline merges the records received from the sensors and uses the merged records to train at least one model used to identify instances of malicious network traffic.
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公开(公告)号:US11588841B2
公开(公告)日:2023-02-21
申请号:US16872077
申请日:2020-05-11
Applicant: Splunk Inc.
Inventor: Kurt Kokko , Damien Lindauer , Brad Lovering , Lynn Kasel
Abstract: Techniques and mechanisms are disclosed for creating an environment for detecting malicious network traffic. A test computer network including a plurality of cloned nodes is created. The plurality of cloned nodes in the test computer network corresponds to at least some of a plurality of target nodes of a host computer network, and the test computer network has no network connectivity to the host computer network. Sensors in both the host computer network and the test computer network generate network flow records that are sent to a detection processing pipeline. The detection processing pipeline merges the records received from the sensors and uses the merged records to train at least one model used to identify instances of malicious network traffic.
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5.
公开(公告)号:US10652261B2
公开(公告)日:2020-05-12
申请号:US15885709
申请日:2018-01-31
Applicant: Splunk Inc.
Inventor: Kurt Kokko , Damien Lindauer , Brad Lovering , Lynn Kasel
Abstract: Techniques and mechanisms are disclosed for creating an environment for detecting malicious network traffic. A test computer network including a plurality of cloned nodes is created. The plurality of cloned nodes in the test computer network corresponds to at least some of a plurality of target nodes of a host computer network, and the test computer network has no network connectivity to the host computer network. Sensors in both the host computer network and the test computer network generate network flow records that are sent to a detection processing pipeline. The detection processing pipeline merges the records received from the sensors and uses the merged records to train at least one model used to identify instances of malicious network traffic.
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