US Patent Application 17660513. Misbehavior Indication Aggregators For Identifying Misbehavior Conditions In Vehicle-To-Everything (V2X) Communication Systems simplified abstract
Misbehavior Indication Aggregators For Identifying Misbehavior Conditions In Vehicle-To-Everything (V2X) Communication Systems
Organization Name
Inventor(s)
Mohammad Raashid Ansari of Lowell MA (US)
Jonathan Petit of Wenham MA (US)
Jean-Philippe Monteuuis of Shrewsbury MA (US)
Cong Chen of Shrewsbury MA (US)
Misbehavior Indication Aggregators For Identifying Misbehavior Conditions In Vehicle-To-Everything (V2X) Communication Systems - A simplified explanation of the abstract
- This abstract for appeared for US patent application number 17660513 Titled 'Misbehavior Indication Aggregators For Identifying Misbehavior Conditions In Vehicle-To-Everything (V2X) Communication Systems'
Simplified Explanation
This abstract describes methods used in vehicle-to-everything (V2X) systems to detect and address misbehavior. Multiple misbehavior detection mechanisms are used to identify indications of misbehavior. These indications are then aggregated to determine if a reportable or actionable misbehavior condition exists. Various techniques are used to aggregate the indications, such as comparing the number of indications to a threshold, applying weights to the indications, or analyzing the number of events classified as misbehavior within a specific time frame or set number of events. Once a misbehavior condition is determined, appropriate actions can be taken.
Original Abstract Submitted
Embodiment methods implemented in vehicle-to-everything (V2X) systems may include detecting multiple indications of V2X misbehavior by multiple misbehavior detection mechanisms, aggregating misbehavior indications output from the misbehavior detection mechanisms, determining whether a reportable or actionable misbehavior condition exists based on aggregated misbehavior indications, and acting on a determined misbehavior condition. Aggregating misbehavior indications may include determining whether any of the misbehavior detection mechanisms outputs a misbehavior indication, determining whether any one of a select subset of the one or more misbehavior detection mechanisms outputs a misbehavior indication, aggregating misbehavior indications output from multiple misbehavior detection mechanisms and comparing the number to a threshold, applying a weight to misbehavior indication outputs and aggregating the weighted outputs, or determining a number of events classified as an attack or misbehavior indications output by each of a plurality of misbehavior detection mechanisms within a window of time or set number of events.
