| Title | Trustworthiness Estimation of Entities within Collective Perception |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Allig, C., Leinmüller, T., Mittal, P., Wanielik, G. |
| Conference Name | 2019 IEEE Vehicular Networking Conference (VNC) |
| Keywords | Bayes filter, Collective perception, collective perception information, composability, Conferences, data consistency, entities trustworthiness estimation, Estimation, host vehicle, intelligent transportation systems, Misbehavior detection, Probabilistic logic, pubcrawl, Radar, reliability, remote vehicle, road safety, sensor fusion, Sensors, situational awareness, telecommunication security, Trusted Computing, trustworthiness, V2X communication, VANET, Vehicle dynamics, vehicle shares information, vehicles awareness, vehicular ad hoc network, vehicular ad hoc networks |
| Abstract | The idea behind collective perception is to improve vehicles' awareness about their surroundings. Every vehicle shares information describing its perceived environment by means of V2X communication. Similar to other information shared using V2X communication, collective perception information is potentially safety relevant, which means there is a need to assess the reliability and quality of received information before further processing. Transmitted information may have been forged by attackers or contain inconsistencies e.g. caused by malfunctions. This paper introduces a novel approach for estimating a belief that a pair of entities, e.g. two remote vehicles or the host vehicle and a remote vehicle, within a Vehicular ad hoc Network (VANET) are both trustworthy. The method updates the belief based on the consistency of the data that both entities provide. The evaluation shows that the proposed method is able to identify forged information. |
| DOI | 10.1109/VNC48660.2019.9062796 |
| Citation Key | allig_trustworthiness_2019 |
Trustworthiness Estimation of Entities within Collective Perception