The evolution of cybersecurity in self-driving cars: insights from bibliometric research

Purpose This study aims to investigate the evolution of cybersecurity in autonomous vehicles over the past decade, focusing on influential publications, leading authors, key themes and emerging research trends. Design/methodology/approach A systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach, with data extracted from The Lens database and analyzed using VOSviewer and Bibliometrix. This study provides a quantitative overview of academic trends from 2014 to 2023. The analysis reveals significant growth in scientific production, predominantly driven by the USA, China and the UK. Central themes include network security, cyberattack prevention and regulatory frameworks. Findings The findings emphasize that cybersecurity, artificial intelligence (AI) and regulation are critical for developing secure and reliable vehicular systems. Research limitations/implications Future research should focus on enhancing security in vehicle-to-everything, vehicle-to-vehicle and vehicle-to-infrastructure communications by improving protocols and integrating AI. Practical implications Key themes identified include trust in security, reliability and user experience. Social implications The analysis highlights future research directions, particularly the integration of AI with sustainable development and autonomous transportation policies. Originality/value This study provides a quantitative overview of academic trends from 2014 to 2023 regarding the theme of cybersecurity and self-driving cars.