SECURITY TECHNIQUES FOR 5G AND NEXT GENERATION RADIO ACCESS NETWORKS

    公开(公告)号:US20210320944A1

    公开(公告)日:2021-10-14

    申请号:US16847031

    申请日:2020-04-13

    Abstract: Malicious attacks by certain devices against a radio access network (RAN) can be detected and mitigated, while allowing communication of priority messages. A security management component (SMC) can determine whether a malicious attack against the RAN is occurring based on a defined baseline that indicates whether a malicious attack is occurring. The defined baseline is determined based on respective characteristics associated with respective devices that are determined based on analysis of information relating to the devices. In response to determining there is a malicious attack, SMC determines whether to block connections of devices to the RAN based on respective priority levels associated with respective messages being communicated by the devices. SMC blocks connections of devices communicating messages associated with priority levels that do not satisfy a defined threshold priority level, while managing communication connections to allow messages satisfying the defined threshold priority level to be communicated via the RAN.

    Short message service congestion manager

    公开(公告)号:US12279153B2

    公开(公告)日:2025-04-15

    申请号:US17453083

    申请日:2021-11-01

    Abstract: The described technology is generally directed towards a short message service (SMS) congestion manager that can evaluate, predict, and mitigate SMS congestion. The SMS congestion manager can be implemented within a short message services function (SMSF) of a fifth generation (5G) or subsequent generation cellular network. The SMS congestion manager can monitor a volume of non-access stratum (NAS) SMS messages in order to detect potential overload conditions wherein the volume of messages exceeds a capability of a network function. In response to detecting potential overload conditions, the SMS congestion manager can inhibit messages directed to the network function in order to prevent overloads from developing. The SMS congestion manager can use machine learning to learn to detect the potential overload conditions as well as to learn actions to take to address the potential overload conditions.

    Scrubbed Internet Protocol Domain for Enhanced Cloud Security

    公开(公告)号:US20230024436A1

    公开(公告)日:2023-01-26

    申请号:US17956930

    申请日:2022-09-30

    Abstract: Concepts and technologies directed to scrubbed internet protocol domain for enhanced cloud security are disclosed herein. In various aspects, a system can include a processor and memory storing instructions that, upon execution, cause performance of operations. The operations can include exposing an application to a service provider network that provides an internet connection, where the application is provided by a datacenter that communicates with the service provider network. The operations can include monitoring traffic flows to the application during an observation time period, where the traffic flows include probe traffic that attempts to reach the application. The operations can include constructing a scrubbed internet protocol domain such that detected probe traffic is prevented from reaching a plurality of virtual machines provided by the datacenter.

    SHORT MESSAGE SERVICE CONGESTION MANAGER

    公开(公告)号:US20230137949A1

    公开(公告)日:2023-05-04

    申请号:US17453083

    申请日:2021-11-01

    Abstract: The described technology is generally directed towards a short message service (SMS) congestion manager that can evaluate, predict, and mitigate SMS congestion. The SMS congestion manager can be implemented within a short message services function (SMSF) of a fifth generation (5G) or subsequent generation cellular network. The SMS congestion manager can monitor a volume of non-access stratum (NAS) SMS messages in order to detect potential overload conditions wherein the volume of messages exceeds a capability of a network function. In response to detecting potential overload conditions, the SMS congestion manager can inhibit messages directed to the network function in order to prevent overloads from developing. The SMS congestion manager can use machine learning to learn to detect the potential overload conditions as well as to learn actions to take to address the potential overload conditions.

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