Author
Azuma, Shuntaro et al.
Benefit Summary HTML

One potential threat to connected-vehicle networks is cloud-based attacks. Such attacks would hijack vehicle-to-cloud (V2C) communications and send falsified information, such as incurring congestion by falsely reporting traffic accidents or fabricating driving and position information.

The authors of the paper offer a method to detect misbehavior from aggregated data on a cloud server by utilizing information from surrounding vehicles. For instance, it is possible to verify the position of a vehicle that reports falsified location data through the independent verification of nearby vehicles that are within the range of vehicle-to-vehicle (V2V) communication. The method proposed within the paper combines this validation with a further cross-reference against local base stations to verify that location information from a given vehicle is accurate. If enough discrepancies are observed, the vehicle is assumed to be transmitting falsified data.

METHOD
To evaluate the effectiveness of the detection procedure, the authors performed a trial using the network simulator Scenargie. A variety of misbehavior methods were examined, to account for possible attempted attacks. The impact of changing the "threshold value," or the number of times the location-validation was performed, was examined.

Hyperlink Exit Door
Yes
Last Modified Date
Pages
11
Publication Sort Date
Publisher
International Journal on Advances in Internet Technology
Result Type
Reviewer
Source ID
1917
Title
A Method of Misbehavior Detection with Mutual Vehicle Position Monitoring
UNID
C62B1D88A3E341FA8525835100697030
Source Review
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