Hybrid Fuzzy and Precise Phase-Based Secret Key Generation for Rail Transit Sensor Networks
Yizhuo Wang, Qinghe Du, Jiyu Chen · 2024
With the advancement of automation and intelligence in rail transit systems, rail transit sensor networks (RTSN) play a crucial role in detection and maintenance, operation status monitoring, and safety protection. However, the open nature of RTSN makes them susceptible to eavesdropping. This paper proposes a novel key generation algorithm that leverages both fuzzy and precise phase. Contrary to conventional secret key generation (SKG) methods that rely on channel characteristics, our approach eliminates the quantization step. Instead, it utilizes the phase of the channel estimation sequence as the fuzzy phase and maps successfully decoded data as the precise phase. By combining these two types of phases, we rotate the constellation points to achieve encrypted transmission of key information. Numerical results demonstrate that our proposed scheme surpasses traditional methods in terms of reliability and security, significantly enhancing the key generation rate, which provides an effective solution for secure communication on RSTN.