Pathloss drop trusted agent misbehavior detection

    公开(公告)号:US12063511B2

    公开(公告)日:2024-08-13

    申请号:US17130631

    申请日:2020-12-22

    CPC classification number: H04W12/104 H04W4/40 H04W12/009

    Abstract: V2X trusted agents provide technical solutions for technical problems facing falsely reported locations of connected vehicles within V2X systems. These trusted agents (e.g., trusted members) may be used to detect an abrupt physical attenuation of a wireless signal and determine whether the attenuation was caused by signal occlusion caused by the presence of an untrusted vehicle or other untrusted object. When the untrusted vehicle is sending a message received by trusted agents, these temporary occlusions allow trusted members to collaboratively estimate the positions of untrusted vehicles in the shared network, and to detect misbehavior by associating the untrusted vehicle with reported positions. Trusted agents may also be used to pinpoint specific mobile targets. Information about one or more untrusted vehicles may be aggregated and distributed as a service.

    Distributed machine learning in an information centric network

    公开(公告)号:US11868858B2

    公开(公告)日:2024-01-09

    申请号:US17892713

    申请日:2022-08-22

    CPC classification number: G06N20/00 H04L67/34

    Abstract: Systems and techniques for distributed machine learning (DML) in an information centric network (ICN) are described herein. Finite message exchanges, such as those used in many DML exercises, may be efficiently implemented by treating certain data packets as interest packets to reduce overall network overhead when performing the finite message exchange. Further, network efficiency in DML may be improved achieved by using local coordinating nodes to manage devices participating in a distributed machine learning exercise. Additionally, modifying a round of DML training to accommodate available participant devices, such as by using a group quality of service metric to select the devices, or extending the round execution parameters to include additional devices, may have an impact on DML performance.

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