A Key Generation Scheme for IoV Communication Based on Neural Network Autoencoders

In recent years, the Internet of Vehicles (IoV) has become more and more widely used. Due to the high dynamic and point-to-point characteristics of IoV communication, IoV needs a secure and effective key generation mechanism. Physical layer key generation has become a promising technology, known for its lightweight and information theory security. IoV communication is usually realized using Wi-Fi, ZigBee, LoRa and other technologies. Based on ESP32 device, this paper explores the use of WiFi communication in the vehicle-to-everything (V2X) scenario of IoV. Focusing on the V2X scenario, we conduct channel modeling based on line of sight (LoS) and multipath fading and present Secure-Vehicle-Key, which is an environment-adaptive key generation scheme using neural network autoencoders. This scheme can realize the dynamic balance of reliability and confidentiality to meet the requirements of different vehicle network situations. Compared with the reconciliation scheme implemented by Slepian-Wolf low-density parity check (LDPC) codes, the method in this paper reduces the bit disagreement rate (BDR) of key generation by 30%-40% and passes the NIST randomness test with excellent results.