Radio Frequency Fingerprint-Based DSRC Intelligent Vehicle Networking Identification Mechanism in High Mobility Environment

Tianshu Chen, Aiqun Hu and Yu Jiang
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Tianshu Chen: School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Aiqun Hu: School of Information Science and Engineering, Southeast University, Nanjing 210096, China
Yu Jiang: The Purple Mountain Laboratories for Network and Communication Security, Nanjing 211111, China

Sustainability, 2022, vol. 14, issue 9, 1-19

Abstract: In recent years, Dedicated Short-Range Communication (DSRC) vehicle interconnection technology has achieved mature development and broad applications, which is the key Vehicle to Everything (V2X) technology to realize transport intelligence. However, the openness of wireless transmission and the mobility of wireless terminals cause the identification mechanism of the DSRC system to face serious security threats. A radio frequency fingerprint (RFF)-based identification method can better resist the identity attack and spoofing by extracting the hardware characteristics formed by the differences of electronic components to authenticate different devices. Therefore, in this paper a novel RFF identification mechanism is proposed for IEEE 802.11p protocol-based DSRC intelligent vehicle networking devices suitable for a high mobility environment, in which the preamble field features of physical layer frames are extracted as device fingerprints, and the random forest algorithm and sequential detection method are used to distinguish and authenticate different devices. The experiment and simulation results demonstrate that the identification accuracy rates of the eight DSRC modules in the low-speed LOS and NLOS experimental states and up to 70 km/h high-speed simulations all exceed 99%, illustrating that this method has important application value in the field of identity authentication of V2X devices in high-speed scenarios.

Keywords: vehicle networking; radio frequency fingerprint; feature extraction; device identification (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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