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公开(公告)号：US12008114B2
公开(公告)日：2024-06-11
申请号：US18139455
申请日：2023-04-26
CPC分类号： G06F21/577 , G06F8/65 , G06N5/04 , G06N20/00 , G06F2221/034
摘要： A machine learning computing system identifies a vulnerability associated with a server. Based on information associated with the server and a knowledge base, the computing system schedules an interval for patching the server in a centralized tracking module. Based on the knowledge base and the vulnerability, the computing system creates, validates, and deploys the patch job. During patch job execution, the computing system monitors the status of the patch job at the server and transmits status updates to a user interface module. After expiration of the interval, the computing system generates an assessment report for the executed patch job. The computing system updates the knowledge base based on the assessment report to improve future decisioning processes. Based on the success or failure of the patch job, the computing system, upon a failure indication, automatically reschedules an interval for patching the server.
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公开(公告)号：US11669621B2
公开(公告)日：2023-06-06
申请号：US16902456
申请日：2020-06-16
CPC分类号： G06F21/577 , G06F8/65 , G06N5/04 , G06N20/00 , G06F2221/034
摘要： A machine learning computing system identifies a vulnerability associated with a server. Based on information associated with the server and a knowledge base, the computing system schedules an interval for patching the server in a centralized tracking module. Based on the knowledge base and the vulnerability, the computing system creates, validates, and deploys the patch job. During patch job execution, the computing system monitors the status of the patch job at the server and transmits status updates to a user interface module. After expiration of the interval, the computing system generates an assessment report for the executed patch job. The computing system updates the knowledge base based on the assessment report to improve future decisioning processes. Based on the success or failure of the patch job, the computing system, upon a failure indication, automatically reschedules an interval for patching the server.
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公开(公告)号：US20240281542A1
公开(公告)日：2024-08-22
申请号：US18651009
申请日：2024-04-30
CPC分类号： G06F21/577 , G06F8/65 , G06N5/04 , G06N20/00 , G06F2221/034
摘要： A machine learning computing system identifies a vulnerability associated with a server. Based on information associated with the server and a knowledge base, the computing system schedules an interval for patching the server in a centralized tracking module. Based on the knowledge base and the vulnerability, the computing system creates, validates, and deploys the patch job. During patch job execution, the computing system monitors the status of the patch job at the server and transmits status updates to a user interface module. After expiration of the interval, the computing system generates an assessment report for the executed patch job. The computing system updates the knowledge base based on the assessment report to improve future decisioning processes. Based on the success or failure of the patch job, the computing system, upon a failure indication, automatically reschedules an interval for patching the server.
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公开(公告)号：US20210390187A1
公开(公告)日：2021-12-16
申请号：US16902456
申请日：2020-06-16
摘要： A machine learning computing system identifies a vulnerability associated with a server. Based on information associated with the server and a knowledge base, the computing system schedules an interval for patching the server in a centralized tracking module. Based on the knowledge base and the vulnerability, the computing system creates, validates, and deploys the patch job. During patch job execution, the computing system monitors the status of the patch job at the server and transmits status updates to a user interface module. After expiration of the interval, the computing system generates an assessment report for the executed patch job. The computing system updates the knowledge base based on the assessment report to improve future decisioning processes. Based on the success or failure of the patch job, the computing system, upon a failure indication, automatically reschedules an interval for patching the server.
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公开(公告)号：US20230259634A1
公开(公告)日：2023-08-17
申请号：US18139455
申请日：2023-04-26
CPC分类号： G06F21/577 , G06N20/00 , G06F8/65 , G06N5/04 , G06F2221/034
摘要： A machine learning computing system identifies a vulnerability associated with a server. Based on information associated with the server and a knowledge base, the computing system schedules an interval for patching the server in a centralized tracking module. Based on the knowledge base and the vulnerability, the computing system creates, validates, and deploys the patch job. During patch job execution, the computing system monitors the status of the patch job at the server and transmits status updates to a user interface module. After expiration of the interval, the computing system generates an assessment report for the executed patch job. The computing system updates the knowledge base based on the assessment report to improve future decisioning processes. Based on the success or failure of the patch job, the computing system, upon a failure indication, automatically reschedules an interval for patching the server.
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公开(公告)号：US20200125775A1
公开(公告)日：2020-04-23
申请号：US16162880
申请日：2018-10-17
发明人： Abhishek Nagpal , Syed Luqman Ahmed
摘要： A data loss prevention device that includes a data loss prevention engine implemented by a processor. The data loss prevention engine is configured to receive data in transit to a target network device and to identify content within the data. The data loss prevention engine is configured to determine the content of the data comprises an image and to determine an image type for the image based on objects within the image, and to determine whether the image type matches a restricted image type from a set of restricted image types. The data loss prevention engine is further configured to block transmission of the data to the target network device in response to determining that the image type matches a restricted image type and forward the data to the target network device in response to determining that the image type does not match a restricted image type.
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公开(公告)号：US12113696B2
公开(公告)日：2024-10-08
申请号：US17590368
申请日：2022-02-01
发明人： Syed Luqman Ahmed , Adi Narayana Rao Garaga , Rakesh Jain , Sidhan Ramadevan Ponnanakkal , Abhay Kumar
IPC分类号： G06F11/00 , G06F3/06 , H04L41/0893 , H04L41/149 , H04L43/0817 , H04L43/16
CPC分类号： H04L43/16 , G06F3/0619 , H04L41/0893 , H04L41/149 , H04L43/0817
摘要： Systems, methods, and computer program products are provided for monitoring network processing using node analysis. The method includes receiving node operation information relating to a node command from one or more nodes. The one or more nodes are grouped into a cluster. The method also includes determining one or more node characteristics based on the node operation information. The method further includes comparing the node characteristic(s) of the node command to expected node characteristic(s). The method still further includes determining a node outage likelihood. The node outage likelihood indicates the likelihood the given node will experience a node outage. The method also includes determining a cluster node operation plan. The cluster node operation plan is configured to determine the nodes of the cluster that must be in operation in an event of the node outage of the given node.
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公开(公告)号：US11586781B2
公开(公告)日：2023-02-21
申请号：US16926688
申请日：2020-07-11
发明人： Abhishek Nagpal , Syed Luqman Ahmed
IPC分类号： G06F21/88 , G06F21/62 , G06N20/00 , G06V30/413
摘要： A data loss prevention device that includes a data loss prevention engine implemented by a processor. The data loss prevention engine is configured to receive data in transit to a target network device and to identify content within the data. The data loss prevention engine is configured to determine the content of the data comprises an image and to determine an image type for the image based on objects within the image, and to determine whether the image type matches a restricted image type from a set of restricted image types. The data loss prevention engine is further configured to block transmission of the data to the target network device in response to determining that the image type matches a restricted image type and forward the data to the target network device in response to determining that the image type does not match a restricted image type.
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公开(公告)号：US20230246938A1
公开(公告)日：2023-08-03
申请号：US17590368
申请日：2022-02-01
发明人： Syed Luqman Ahmed , Adi Narayana Rao Garaga , Rakesh Jain , Sidhan Ramadevan Ponnanakkal , Abhay Kumar
IPC分类号： G06F3/06
CPC分类号： G06F3/0617 , G06F3/0619 , G06F3/0659 , G06F3/067
摘要： Systems, methods, and computer program products are provided for monitoring network processing using node analysis. The method includes receiving node operation information relating to a node command from one or more nodes. The one or more nodes are grouped into a cluster. The method also includes determining one or more node characteristics based on the node operation information. The method further includes comparing the node characteristic(s) of the node command to expected node characteristic(s). The method still further includes determining a node outage likelihood. The node outage likelihood indicates the likelihood the given node will experience a node outage. The method also includes determining a cluster node operation plan. The cluster node operation plan is configured to determine the nodes of the cluster that must be in operation in an event of the node outage of the given node.
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公开(公告)号：US20200349298A1
公开(公告)日：2020-11-05
申请号：US16926688
申请日：2020-07-11
发明人： Abhishek Nagpal , Syed Luqman Ahmed
摘要： A data loss prevention device that includes a data loss prevention engine implemented by a processor. The data loss prevention engine is configured to receive data in transit to a target network device and to identify content within the data. The data loss prevention engine is configured to determine the content of the data comprises an image and to determine an image type for the image based on objects within the image, and to determine whether the image type matches a restricted image type from a set of restricted image types. The data loss prevention engine is further configured to block transmission of the data to the target network device in response to determining that the image type matches a restricted image type and forward the data to the target network device in response to determining that the image type does not match a restricted image type.
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