Misbehavior Detection Using Collective Perception under Privacy Considerations
This addresses security and privacy trade-offs in vehicle-to-vehicle communication for ITS, though it is incremental as it builds on existing standards like CPM.
The paper tackled the challenge of detecting misbehavior in cooperative ITS while preserving privacy, by using collective perception messages (CPM) from other vehicles. The result was a reduction in the false positive rate by approximately 15 percentage points while maintaining true positive detection.
In cooperative ITS, security and privacy protection are essential. Cooperative Awareness Message (CAM) is a basic V2V message standard, and misbehavior detection is critical for protection against attacking CAMs from the inside system, in addition to node authentication by Public Key Infrastructure (PKI). On the contrary, pseudonym IDs, which have been introduced to protect privacy from tracking, make it challenging to perform misbehavior detection. In this study, we improve the performance of misbehavior detection using observation data of other vehicles. This is referred to as collective perception message (CPM), which is becoming the new standard in European countries. We have experimented using realistic traffic scenarios and succeeded in reducing the rate of rejecting valid CAMs (false positive) by approximately 15 percentage points while maintaining the rate of correctly detecting attacks (true positive).