NETWORK TRAFFIC FORECASTING FOR NON-TICKETED EVENTS

    公开(公告)号:US20200077282A1

    公开(公告)日:2020-03-05

    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.

    Correlating compromised home internet of things devices with distributed denial of service attacks

    公开(公告)号:US12160445B2

    公开(公告)日:2024-12-03

    申请号:US17724112

    申请日:2022-04-19

    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.

    Detecting and Mitigating Drive-by Home Wi-Fi Hijack Attacks

    公开(公告)号:US20230362650A1

    公开(公告)日:2023-11-09

    申请号:US17735691

    申请日:2022-05-03

    CPC classification number: H04W12/122 H04W88/16

    Abstract: The concepts and technologies disclosed herein are directed detecting and mitigating drive-by home WI-FI hijack attacks. According to one aspect, a war driving activity correlation system can obtain a report from a home gateway system. The report can identify a suspicious device attempting to connect to a WI-FI network provided, at least in part, by the home gateway system. The war driving activity correlation system can determine, based upon the report, a route of an attacker who uses the suspicious device. The war driving activity correlation system can send instructions to the home gateway system. The instructions can include the route and can specify one or more mitigation actions to be performed by the home gateway system, such as blacklisting a media access control address associated with the suspicious device. The mitigation action(s) can be based upon one or more policies.

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

    公开(公告)号:US20230336585A1

    公开(公告)日:2023-10-19

    申请号:US17724112

    申请日:2022-04-19

    CPC classification number: H04L63/1458 H04L63/0209 H04L2463/141 G16Y30/10

    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.

    NETWORK TRAFFIC FORECASTING FOR NON-TICKETED EVENTS

    公开(公告)号:US20220060911A1

    公开(公告)日:2022-02-24

    申请号:US17454045

    申请日:2021-11-08

    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.

    BEAM PROVISIONING FOR SENSORY DATA COLLECTION FOR 5G OR OTHER NEXT GENERATION NETWORKS

    公开(公告)号:US20210105720A1

    公开(公告)日:2021-04-08

    申请号:US17102892

    申请日:2020-11-24

    Abstract: Deployment of Internet-of-things devices can comprise sensors deployed in remote and hard to reach areas and locations. Due to lack of access to reliable power, these sensors cannot always be connected to a network and also have limited computation power. Consequently, a mechanism can be established to periodically access these sensors and collect data from them. The mechanism can utilize a mobile radio unit device to serve as data collectors. The mobile radio unit device can make use of an adaptive beam scanning to perform sensory data collection via the beam scanning operation. Additionally, the platform can also comprise a radio access network intelligent controller to manage the data collecting radio units by providing specific instructions and data collection methodologies.

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