Decoding Vehicle Motion Data on the Internal Network

Abstract

Encrypting functions of vehicle internal networks make the lives of third parties more difficult since, in most cases, the meaning of messages carried by the CAN bus is not disclosed This paper proposes a reverse engineering method to discover, to a large extent, the semantics of CAN messages in a vehicle internal network. A filtering mechanism has been applied that includes several statistical processes to interpret the codes of CAN messages. The speed change function of a vehicle has been chosen as an example to be followed in the development steps of this approach to predict the motion mechanism of the vehicle. The selected codes were verified by developing a multilevel model that relates the hierarchical relationship between the bytes and IDs and their impact on the speed factor. The most influential IDs and bytes on vehicle speed function were: ID 512, ID 520, ID 664, and B2, B4, B6, respectively. The selected codes used to model the observed speed do not mean they all share the speed function, but there is a good possibility that at least some fulfill this function. However, the same methodology can be applied, with some optimization, to detect other semantic messages in the CAN network based on the expected type of data.