WIRELESS NETWORK COVERAGE BASED ON A PREDETERMINED DEVICE CLUSTER MODEL SELECTED ACCORDING TO A CURRENT KEY PERFORMANCE INDICATOR

    公开(公告)号:US20200322814A1

    公开(公告)日:2020-10-08

    申请号:US16374719

    申请日:2019-04-03

    Abstract: Adapting wireless network coverage areas according to beam parameters corresponding to predetermined radio cluster models is disclosed. The disclosed subject matter can enable determining cluster models corresponding to historic use of a wireless network, e.g., based on historical KPIs, etc., from UEs, RAN devices, antennas, and other sources. The cluster models can correspond to beam parameters. The cluster model of the cluster models can be selected based on a current KPI value, e.g., a real-time or near real-time wireless network measurement, e.g., from a UE, RAN device, antenna, etc. Beam parameters corresponding to the selected cluster model can be communicated to a RAN device which can generate a corresponding radio beam. In an aspect, this can provide wireless connectivity to clusters of devices in the area of the radio beam, wherein the devices of the clusters can, in some embodiments, share same or similar wireless network demands.

    Correlating Compromised Home Internet of Things Devices With Distributed Denial of Service Attacks

    公开(公告)号:US20250097262A1

    公开(公告)日:2025-03-20

    申请号:US18964834

    申请日:2024-12-02

    Abstract: A distributed denial of service (“DDoS”) attack profiler can determine a plurality of DDoS attack properties associated with a DDoS attack that utilizes an Internet of Things (“IoT”) device operating in communication with a home gateway. The DDoS attack profiler can create a DDoS attack profile and can provide a DDoS attack report based upon the DDoS attack profile to a correlator. An IoT device profiler can determine a plurality of IoT device properties and can create, based upon the plurality of IoT device properties, an IoT device profile. The IoT device profiler can create an anomaly report that identifies an anomaly associated with the IoT device. The correlator can correlate the DDoS attack report with the anomaly report to determine if a match exists. In response to determining that the match exists, the home gateway system can store the bot match record in a bot match repository.

    Home Gateway Monitoring for Vulnerable Home Internet of Things Devices

    公开(公告)号:US20230308467A1

    公开(公告)日:2023-09-28

    申请号:US17702858

    申请日:2022-03-24

    CPC classification number: H04L63/1433 G16Y30/10 H04L63/105

    Abstract: The concepts and technologies disclosed herein are directed to home gateway monitoring for vulnerable home Internet of Things (“IoT”) devices. According to one aspect disclosed herein, a home gateway can scan a home network address space of a home network for an IoT device. The home gateway can perform a vulnerability test on the IoT device to determine whether the IoT device is vulnerable to a known vulnerability. In response to determining that the IoT device is vulnerable to the known vulnerability, the home gateway can change a device status of the IoT device to a vulnerable status and can change a permissions level of the IoT device to a quarantine permissions level.

    Network traffic forecasting for non-ticketed events

    公开(公告)号:US11172381B2

    公开(公告)日:2021-11-09

    申请号:US16679732

    申请日:2019-11-11

    Abstract: An example method includes estimating a number of people expected to attend a non-ticketed event, based on electronic data including social media postings, estimating a per-person amount of network traffic expected to be generated on a communications network during the non-ticketed event, based at least in part on historical per-person network traffic statistics for a historical event of a similar type to the non-ticketed event, calculating an amount of total network traffic expected to be generated during the non-ticketed event, based at least on the number of people expected to attend the non-ticketed event and the per-person amount of network traffic, and implementing a modification to an infrastructure of the communications network in a geographic location of the non-ticketed event, based at least in part on the amount of total network traffic expected to be generated during the non-ticketed event.

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