Context-Bound Cybersecurity Framework for Resisting Eavesdropping in Vehicle Networks

Wireless channels that are widely adopted between autonomous vehicles are vulnerable to eavesdropping or interferences, so that attacks on cybersecurity may lead to serious consequences, such as losing control of vehicles. In particular, the cryptographic methods used for information security rely on the strict privacy of keys, which is often difficult to guarantee in a wireless environment. This paper proposes a context-bound cybersecurity framework, which protects communication from eavesdroppers by encrypting critical data with a dynamic context among vehicles. The context is synchronized among vehicles through a progressive encoding method, which makes it difficult for third parties to learn the entire context by eavesdropping through the channels, especially in the case of mobility. The normal vehicles may extract a security key from the context to encrypt and decrypt key data, but it is impossible or overwhelmingly expensive for the third parties to decode the data transmitted due to the lack of the context. Besides, the proposed framework also provides a promising way to resist the upcoming quantum computers, because it will become more and more difficult for third parties to collect the complete context as the context continues to update.