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一项针对自动化车辆部署的感知网络安全障碍的跨国实证研究。

A multinational empirical study of perceived cyber barriers to automated vehicles deployment.

机构信息

School of Engineering, RMIT University, Melbourne, Australia.

RMIT University, Melbourne, Australia.

出版信息

Sci Rep. 2023 Feb 1;13(1):1842. doi: 10.1038/s41598-023-29018-9.

DOI:10.1038/s41598-023-29018-9
PMID:36725959
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9892035/
Abstract

The digital transformation of Automated Vehicles (AVs) has raised concerns in the cyber realm among prospective AV consumers. However, there is a dearth of empirical research on how cyber obstacles may impact the operation of AVs. To address this knowledge gap, this study examines the six critical cyber impediments (data privacy, AV connectivity, ITS infrastructure, lack of cybersecurity regulations, AV cybersecurity understanding, and AV cyber-insurance) that influence the deployment of AVs. The impact of gender, age, income level, and individual AV and cybersecurity knowledge on these obstacles are statistically assessed using a sample of 2061 adults from the United States, the United Kingdom, New Zealand, and Australia. The research revealed intriguing empirical findings on all cyber barriers in the form of a trichotomy: participants' education level, understanding of AVs, and cybersecurity knowledge. As education levels increase, the significance of a cyber barrier to AV deployment decreases; however, as AV comprehension and cybersecurity knowledge increase, the perception of a cyber barrier becomes significantly more important. In addition, the study demonstrates differences in perceptions of cyber barriers and AV deployments based on gender, age, income, and geographic location. This study's findings on cyber barriers and AV deployment have implications for academia and industry.

摘要

自动驾驶汽车(AV)的数字化转型在潜在的 AV 消费者中引起了网络领域的关注。然而,关于网络障碍如何影响 AV 的运行,实证研究还很少。为了弥补这一知识空白,本研究考察了影响 AV 部署的六个关键网络障碍(数据隐私、AV 连接、ITS 基础设施、缺乏网络安全法规、AV 网络安全理解和 AV 网络安全保险)。本研究使用来自美国、英国、新西兰和澳大利亚的 2061 名成年人样本,统计评估了性别、年龄、收入水平以及个人对 AV 和网络安全知识对这些障碍的影响。研究结果以三分法的形式揭示了所有网络障碍的有趣实证发现:参与者的教育水平、对 AV 的理解和网络安全知识。随着教育水平的提高,网络障碍对 AV 部署的重要性降低;然而,随着对 AV 的理解和网络安全知识的增加,网络障碍的感知变得更加重要。此外,该研究还展示了基于性别、年龄、收入和地理位置的网络障碍和 AV 部署感知的差异。本研究关于网络障碍和 AV 部署的研究结果对学术界和工业界具有重要意义。

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本文引用的文献

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2
Using Automated Vehicle Technologies With Older Adults: A Mixed-Methods Study.使用自动驾驶汽车技术辅助老年人:一项混合方法研究。
OTJR (Thorofare N J). 2022 Jul;42(3):189-198. doi: 10.1177/15394492221082493. Epub 2022 Mar 30.
3
A conceptual system dynamics model for cybersecurity assessment of connected and autonomous vehicles.面向车联网和自动驾驶汽车网络安全评估的概念系统动力学模型。
Accid Anal Prev. 2022 Feb;165:106515. doi: 10.1016/j.aap.2021.106515. Epub 2021 Dec 8.
4
Cyber-attacks in the next-generation cars, mitigation techniques, anticipated readiness and future directions.下一代汽车中的网络攻击、缓解技术、预期就绪情况和未来方向。
Accid Anal Prev. 2020 Dec;148:105837. doi: 10.1016/j.aap.2020.105837. Epub 2020 Oct 26.
5
Personal identifiability of user tracking data during observation of 360-degree VR video.在观察 360 度 VR 视频时对用户跟踪数据的个人可识别性。
Sci Rep. 2020 Oct 15;10(1):17404. doi: 10.1038/s41598-020-74486-y.
6
The Proposal to Lower P Value Thresholds to .005.将P值阈值降至0.005的提议。
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