Consumers’ attitudes toward information security threats against connected and autonomous vehicles

Kyuho Maeng, Woojae Kim, Youngsang Cho

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Connected and autonomous vehicles (CAVs) and intelligent transport systems are transforming individual driving behavior and thus, the vehicle industry and transport sector. However, increasing vehicle connectivity makes CAVs more susceptible to cyber-attacks, which is a barrier to consumers’ CAV adoption. This study analyzes the types of information security threats consumers consider to be the most dangerous and consumer preference for the information security solution that protects their CAVs from such information security threats. We use stated preference data from a discrete choice experiment and a mixed logit model to reflect consumers’ heterogeneity on information security threats and solutions. Furthermore, we investigate the effects of experiencing privacy leakage on attitudes toward CAV information security threats by dividing respondents into two groups. The results show that consumers regard communication failure and the unauthorized collection of personal information as dangerous information security threats, which implies that confidentiality and availability are more essential to CAV security than other factors. Moreover, convenience of use, such as having automatic updates and a security dashboard, is also important when purchasing a CAV information security solution. We also find that respondents who have experienced privacy leakage have a higher preference for protecting CAVs from information security threats than those who have not.

Original languageEnglish
Article number101646
JournalTelematics and Informatics
Volume63
DOIs
Publication statusPublished - 2021 Oct

Bibliographical note

Funding Information:
This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. NRF-2016R1A2B4009990).

Publisher Copyright:
© 2021 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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