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公开(公告)号:US12126504B2
公开(公告)日:2024-10-22
申请号:US18175426
申请日:2023-02-27
Applicant: Juniper Networks, Inc.
Inventor: Anders Bergsten , Mikael Sundström
IPC: H04L43/02
CPC classification number: H04L43/02
Abstract: A method of measuring (100) metrics of a computer network, comprising the steps of:
from a data source collecting (110) sets of data points during a sampling time period, wherein the set of data points constitute a sample, and uploading (120) each sample to a server for further processing (130), wherein from each sample, a fractile information instance is produced (131), wherein the fractile information has a type and each data source is associated (110a) with a fractile information type.-
公开(公告)号:US20240283719A1
公开(公告)日:2024-08-22
申请号:US18112416
申请日:2023-02-21
Applicant: Kyndryl, Inc.
Inventor: Kalpesh Sharma , Muniyandi Perumal Thevar , Shaleen Tongia , Nalini M
IPC: H04L43/0817 , H04L43/02
CPC classification number: H04L43/0817 , H04L43/02
Abstract: A computer-implemented method, in accordance with one embodiment, includes receiving a taxonomy specifying entities of a business service and levels of said entities. Time series data about the entities is collected and stored. Impactor propagation paths between entities is identified. A territory of a health impact of each entity is also identified. A health score for each of the entities, considering impacts on a health of the entity by at least one other entity, is computed based on the data, the propagation paths, and the territories of the entities. At least one of the health scores is output.
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公开(公告)号:US20240259844A1
公开(公告)日:2024-08-01
申请号:US18564073
申请日:2021-05-31
Applicant: Telefonaktiebolaget LM Ericsson (publ)
Inventor: Attila BÁDER , Gergely DÉVAI , Peter SCHVARCZ-FEKETE , Andras SOLYMOSI , Virag WEILER , József MALA
Abstract: We generally describe a method for generating key performance indicator data for network monitoring in a mobile telecommunication network. The method includes providing, relative to an event in the mobile telecommunication network, one or both of a first priority value of a key performance indicator and a second priority value of a key performance indicator dimension. The method further includes determining, based on one or both of the first priority value and the second priority value, whether to generate the key performance indicator data for the network monitoring in the mobile telecommunication network.
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公开(公告)号:US20240243982A1
公开(公告)日:2024-07-18
申请号:US18096340
申请日:2023-01-12
Applicant: VMware, Inc.
Inventor: Kannan Parthasarathy
Abstract: Disclosed are various examples for automatically analyzing telemetry data from managed devices in one or more organizations and categorizing devices and/or user accounts as home users, hybrid users, or office users. The categorization can be performed based upon an analysis of a wireless network connection of a client device that is managed by a management service.
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公开(公告)号:US20240205118A1
公开(公告)日:2024-06-20
申请号:US18593403
申请日:2024-03-01
Applicant: Cisco Technology, Inc.
Inventor: Sunil Kumar Gupta , Navindra Yadav , Michael Standish Watts , Ali Parandehgheibi , Shashidhar Gandham , Ashutosh Kulshreshtha , Khawar Deen
IPC: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/455 , G06F16/11 , G06F16/13 , G06F16/16 , G06F16/17 , G06F16/174 , G06F16/23 , G06F16/2457 , G06F16/248 , G06F16/28 , G06F16/29 , G06F16/9535 , G06F21/53 , G06F21/55 , G06F21/56 , G06N20/00 , G06N99/00 , G06T11/20 , H04J3/06 , H04J3/14 , H04L1/24 , H04L7/10 , H04L9/08 , H04L9/32 , H04L9/40 , H04L41/046 , H04L41/0668 , H04L41/0803 , H04L41/0806 , H04L41/0816 , H04L41/0893 , H04L41/12 , H04L41/16 , H04L41/22 , H04L43/02 , H04L43/026 , H04L43/04 , H04L43/062 , H04L43/08 , H04L43/0805 , H04L43/0811 , H04L43/0829 , H04L43/0852 , H04L43/0864 , H04L43/0876 , H04L43/0882 , H04L43/0888 , H04L43/10 , H04L43/106 , H04L43/12 , H04L43/16 , H04L45/00 , H04L45/302 , H04L45/50 , H04L45/74 , H04L47/11 , H04L47/20 , H04L47/2441 , H04L47/2483 , H04L47/28 , H04L47/31 , H04L47/32 , H04L61/5007 , H04L67/01 , H04L67/10 , H04L67/1001 , H04L67/12 , H04L67/50 , H04L67/51 , H04L67/75 , H04L69/16 , H04L69/22 , H04W72/54 , H04W84/18
CPC classification number: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/45558 , G06F16/122 , G06F16/137 , G06F16/162 , G06F16/17 , G06F16/173 , G06F16/174 , G06F16/1744 , G06F16/1748 , G06F16/2322 , G06F16/235 , G06F16/2365 , G06F16/24578 , G06F16/248 , G06F16/285 , G06F16/288 , G06F16/29 , G06F16/9535 , G06F21/53 , G06F21/552 , G06F21/556 , G06F21/566 , G06N20/00 , G06N99/00 , G06T11/206 , H04J3/0661 , H04J3/14 , H04L1/242 , H04L7/10 , H04L9/0866 , H04L9/3239 , H04L9/3242 , H04L41/046 , H04L41/0668 , H04L41/0803 , H04L41/0806 , H04L41/0816 , H04L41/0893 , H04L41/12 , H04L41/16 , H04L41/22 , H04L43/02 , H04L43/026 , H04L43/04 , H04L43/062 , H04L43/08 , H04L43/0805 , H04L43/0811 , H04L43/0829 , H04L43/0841 , H04L43/0858 , H04L43/0864 , H04L43/0876 , H04L43/0882 , H04L43/0888 , H04L43/10 , H04L43/106 , H04L43/12 , H04L43/16 , H04L45/306 , H04L45/38 , H04L45/46 , H04L45/507 , H04L45/66 , H04L45/74 , H04L47/11 , H04L47/20 , H04L47/2441 , H04L47/2483 , H04L47/28 , H04L47/31 , H04L47/32 , H04L61/5007 , H04L63/0227 , H04L63/0263 , H04L63/06 , H04L63/0876 , H04L63/1408 , H04L63/1416 , H04L63/1425 , H04L63/1433 , H04L63/1441 , H04L63/145 , H04L63/1458 , H04L63/1466 , H04L63/16 , H04L63/20 , H04L67/01 , H04L67/10 , H04L67/1001 , H04L67/12 , H04L67/51 , H04L67/75 , H04L69/16 , H04L69/22 , H04W72/54 , H04W84/18 , G06F2009/4557 , G06F2009/45587 , G06F2009/45591 , G06F2009/45595 , G06F2221/033 , G06F2221/2101 , G06F2221/2105 , G06F2221/2111 , G06F2221/2115 , G06F2221/2145 , H04L67/535
Abstract: A method provides for receiving network traffic from a host having a host IP address and operating in a data center, and analyzing a malware tracker for IP addresses of hosts having been infected by a malware to yield an analysis. When the analysis indicates that the host IP address has been used to communicate with an external host infected by the malware to yield an indication, the method includes assigning a reputation score, based on the indication, to the host. The method can further include applying a conditional policy associated with using the host based on the reputation score. The reputation score can include a reduced reputation score from a previous reputation score for the host.
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公开(公告)号:US11996997B2
公开(公告)日:2024-05-28
申请号:US17779690
申请日:2020-11-27
Applicant: TELECOM ITALIA S.p.A.
Inventor: Mauro Cociglio
IPC: H04L43/0829 , H04L43/02 , H04L43/062 , H04L43/0852
CPC classification number: H04L43/0829 , H04L43/02 , H04L43/062 , H04L43/0852
Abstract: In a method for exchanging packets between first and second nodes of a packet-switched network, each packet comprises two fields settable to an idle value or measurement value. The first node transmits to the second node first packets having a filed set to measurement value. Upon reception of each first packet, the second node transmits back to the first node a second packet having a field set to measurement value. Upon reception of each second packet, the first node transmits to the second node a third packet having another field set to measurement value. A packet loss measurement is calculated as a difference between the number of first packets and the number of third packets.
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公开(公告)号:US11934296B2
公开(公告)日:2024-03-19
申请号:US17725147
申请日:2022-04-20
Applicant: Oracle International Corporation
Inventor: Raghu Hanumanth Reddy Patti , Christopher A. Roy , Ana Maria Hernandez McCollum , Manas Goswami
IPC: G06F11/00 , G06F11/07 , G06F11/30 , G06F11/34 , G06F11/36 , G06Q10/0631 , G06Q10/0633 , G06Q10/0637 , G06Q10/10 , G06Q10/20 , H04L43/02 , H04L67/00 , H04L67/50
CPC classification number: G06F11/3636 , G06F11/079 , G06F11/0793 , G06F11/3051 , G06F11/3065 , G06F11/3438 , G06F11/3466 , G06F11/3495 , G06F11/366 , G06Q10/06316 , G06Q10/0633 , G06Q10/0637 , G06Q10/103 , G06Q10/20 , H04L43/02 , G06F2201/86 , H04L67/00 , H04L67/535
Abstract: Techniques for generating supplemental information based on runbook operation results are disclosed. A system generates and displays supplemental information for a runbook execution interface based on one of a system component associated with an executable operation of a runbook, and a set of runbook operation results corresponding to the executable operation. The system receives a user input to execute an operation defined by a runbook presented to remediate an event. The system generates supplemental information for the runbook execution interface based on the results of the operation executed by the user. The system identifies characteristics associated with the runbook operation results and identifies sources for additional information. Source may include performance data from the same component over a different period of time, performance data of a similar component, and performance data of topologically-connected components.
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公开(公告)号:US11924069B2
公开(公告)日:2024-03-05
申请号:US17581208
申请日:2022-01-21
Applicant: Dell Products L.P.
Inventor: Ben Fauber
IPC: G06F15/173 , G06F18/20 , H03M7/30 , H04L43/02 , H04L43/04
CPC classification number: H04L43/02 , G06F18/20 , H03M7/3059 , H03M7/70 , H04L43/04
Abstract: A system can identify a first group of time-series telemetry data that represents performance metrics of a computing device, wherein the first group of time-series telemetry data identifies respective first values and corresponding respective first timestamps. The system can create a second group of time-series telemetry data that identifies second timestamps. The system can populate the second group of time-series telemetry data with the respective first values at respective first locations of the second group of time-series telemetry data that correspond to the respective first timestamps of the respective first values. The system can create a tensor that identifies third timestamps. The system can populate the tensor with the respective first values at respective second locations of the tensor that correspond to the respective first timestamps of the respective first values, wherein populating the tensor comprises combining two values of the respective first values.
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公开(公告)号:US11902121B2
公开(公告)日:2024-02-13
申请号:US17822656
申请日:2022-08-26
Applicant: Cisco Technology, Inc.
Inventor: Khawar Deen , Navindra Yadav , Anubhav Gupta , Shashidhar Gandham , Rohit Chandra Prasad , Abhishek Ranjan Singh , Shih-Chun Chang
IPC: H04L9/40 , G06F16/00 , G06F21/60 , H04L43/045 , G06F9/455 , G06N20/00 , G06F21/55 , G06F21/56 , G06F16/28 , G06F16/2457 , G06F16/248 , G06F16/29 , G06F16/16 , G06F16/17 , G06F16/11 , G06F16/13 , G06F16/174 , G06F16/23 , G06F16/9535 , G06N99/00 , H04L9/32 , H04L41/0668 , H04L43/0805 , H04L43/0811 , H04L43/0852 , H04L43/106 , H04L45/00 , H04L45/50 , H04L67/12 , H04L43/026 , H04L61/5007 , H04L67/01 , H04L67/51 , H04L67/75 , H04L67/1001 , H04W72/54 , H04L43/062 , H04L43/10 , H04L47/2441 , H04L41/0893 , H04L43/08 , H04L43/04 , H04W84/18 , H04L67/10 , H04L41/046 , H04L43/0876 , H04L41/12 , H04L41/16 , H04L41/0816 , G06F21/53 , H04L41/22 , G06F3/04842 , G06F3/04847 , H04L41/0803 , H04L43/0829 , H04L43/16 , H04L1/24 , H04L9/08 , H04J3/06 , H04J3/14 , H04L47/20 , H04L47/32 , H04L43/0864 , H04L47/11 , H04L69/22 , H04L45/74 , H04L47/2483 , H04L43/0882 , H04L41/0806 , H04L43/0888 , H04L43/12 , H04L47/31 , G06F3/0482 , G06T11/20 , H04L43/02 , H04L47/28 , H04L69/16 , H04L45/302 , H04L67/50
CPC classification number: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/45558 , G06F16/122 , G06F16/137 , G06F16/162 , G06F16/17 , G06F16/173 , G06F16/174 , G06F16/1744 , G06F16/1748 , G06F16/235 , G06F16/2322 , G06F16/2365 , G06F16/248 , G06F16/24578 , G06F16/285 , G06F16/288 , G06F16/29 , G06F16/9535 , G06F21/53 , G06F21/552 , G06F21/556 , G06F21/566 , G06N20/00 , G06N99/00 , G06T11/206 , H04J3/0661 , H04J3/14 , H04L1/242 , H04L9/0866 , H04L9/3239 , H04L9/3242 , H04L41/046 , H04L41/0668 , H04L41/0803 , H04L41/0806 , H04L41/0816 , H04L41/0893 , H04L41/12 , H04L41/16 , H04L41/22 , H04L43/02 , H04L43/026 , H04L43/04 , H04L43/062 , H04L43/08 , H04L43/0805 , H04L43/0811 , H04L43/0829 , H04L43/0841 , H04L43/0858 , H04L43/0864 , H04L43/0876 , H04L43/0882 , H04L43/0888 , H04L43/10 , H04L43/106 , H04L43/12 , H04L43/16 , H04L45/306 , H04L45/38 , H04L45/46 , H04L45/507 , H04L45/66 , H04L45/74 , H04L47/11 , H04L47/20 , H04L47/2441 , H04L47/2483 , H04L47/28 , H04L47/31 , H04L47/32 , H04L61/5007 , H04L63/0227 , H04L63/0263 , H04L63/06 , H04L63/0876 , H04L63/145 , H04L63/1408 , H04L63/1416 , H04L63/1425 , H04L63/1433 , H04L63/1441 , H04L63/1458 , H04L63/1466 , H04L63/16 , H04L63/20 , H04L67/01 , H04L67/10 , H04L67/1001 , H04L67/12 , H04L67/51 , H04L67/75 , H04L69/16 , H04L69/22 , H04W72/54 , H04W84/18 , G06F2009/4557 , G06F2009/45587 , G06F2009/45591 , G06F2009/45595 , G06F2221/033 , G06F2221/2101 , G06F2221/2105 , G06F2221/2111 , G06F2221/2115 , G06F2221/2145 , H04L67/535
Abstract: A method includes capturing first data associated with a first packet flow originating from a first host using a first capture agent deployed at the first host to yield first flow data, capturing second data associated with a second packet flow originating from the first host from a second capture agent deployed on a second host to yield second flow data and comparing the first flow data and the second flow data to yield a difference. When the difference is above a threshold value, the method includes determining that the second packet flow was transmitted by a component that bypassed an operating stack of the first host or a packet capture agent at the device to yield a determination, detecting that hidden network traffic exists, and predicting a malware issue with the first host based on the determination.
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公开(公告)号:US20240031243A1
公开(公告)日:2024-01-25
申请号:US18469952
申请日:2023-09-19
Applicant: Bank of America Corporation
Inventor: Stephen Jack Williams , Richard Scot , Rebecca Lynn Pietro , John Shelton , Abelardo Espinoza , Nathan Alexander Dalpini , Vani Reddy Nareddy
IPC: H04L41/16 , H04L67/306 , H04L43/04 , H04L43/062 , H04L43/02
CPC classification number: H04L41/16 , H04L67/306 , H04L43/04 , H04L43/062 , H04L43/02
Abstract: A system for predicting an anomalous request comprises a processor associated with a server. The processor is configured to generate a first set of data objects associated with a first user profile. The processor is configured to compare the first set of the data objects to approved data and audit data to generate a second set of data objects with a set of anomalous data indicators for the first user profile. The processor is further configured to process the second set of the data objects through an anomaly learning model to determine a predictive degree of approval associated with the user profile. The processor is further configured to determine to how to process the user profile based on the predictive degree of approval. The processor is further configured to assign a profile indicator to the user profile.
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