Chaotic and Random Neural Network Cipher for In-Vehicle Network Security

Abstract

With the proliferation of automotive electronic devices, electronic control units are increasingly used to share information within in-vehicle networks. This induces a range of security risks, such as information disclosure, spoofing, and tampering. In this paper, we propose a symmetric-key cipher. The method generates pseudo-random numbers using a chaotic and random neural network, and encrypts and decrypts frame messages of in-vehicle networks based on the symmetric key. We also propose a lightweight ID-based key sharing protocol. We evaluated the key sharing, encryption, and decryption in Controller Area Network.