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A Quantitative Analysis of Autonomous Vehicle Cybersecurity as a Component of Trust.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Quantitative Analysis of Autonomous Vehicle Cybersecurity as a Component of Trust./
作者:	King, Warren A.
面頁冊數:	1 online resource (163 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Contained By:	Dissertations Abstracts International84-04B.
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29395747click for full text (PQDT)
ISBN:	9798351454597

A Quantitative Analysis of Autonomous Vehicle Cybersecurity as a Component of Trust.
King, Warren A.

A Quantitative Analysis of Autonomous Vehicle Cybersecurity as a Component of Trust. - 1 online resource (163 pages)

Source: Dissertations Abstracts International, Volume: 84-04, Section: B.

Thesis (D.Sc.)--Capitol Technology University, 2022.

Includes bibliographical references

Connected vehicles are technologically complex, which makes them vulnerable to cyber-attacks. Many cybersecurity researchers, white hat hackers, and black hat hackers have discovered numerous exploitable vulnerabilities in connected vehicles. Several studies indicate consumers do not fully trust automated driving systems. The automotive industry understands that gaining consumer trust is vital to the acceptance of autonomous vehicles; however, trust is complex and multifaceted. However, perceptions of cyber threats were not considered to be a component of trust. This quantitative non-experimental dissertation research study explored the magnitude of influence autonomous vehicle cyber threats have on trust. The study expanded the technology acceptance model (TAM) to include cybersecurity and level of trust as determinants of technology acceptance. This study surveyed a diverse sample of 209 licensed U.S. drivers over 18 years old. Results indicated that perceived ease of use positively influences perceived usefulness, perceived ease of usefulness negatively influences perceived cyber threats, and perceived cyber threats negatively influence the level of trust. This research introduced a new application of the TAM and provides the automotive industry with quantifiable metrics that link cybersecurity perceptions to increasing trust in autonomous vehicles.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798351454597Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Autonomous vehiclesIndex Terms--Genre/Form:

542853
Electronic books.

A Quantitative Analysis of Autonomous Vehicle Cybersecurity as a Component of Trust.
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504 $a Includes bibliographical references
520 $a Connected vehicles are technologically complex, which makes them vulnerable to cyber-attacks. Many cybersecurity researchers, white hat hackers, and black hat hackers have discovered numerous exploitable vulnerabilities in connected vehicles. Several studies indicate consumers do not fully trust automated driving systems. The automotive industry understands that gaining consumer trust is vital to the acceptance of autonomous vehicles; however, trust is complex and multifaceted. However, perceptions of cyber threats were not considered to be a component of trust. This quantitative non-experimental dissertation research study explored the magnitude of influence autonomous vehicle cyber threats have on trust. The study expanded the technology acceptance model (TAM) to include cybersecurity and level of trust as determinants of technology acceptance. This study surveyed a diverse sample of 209 licensed U.S. drivers over 18 years old. Results indicated that perceived ease of use positively influences perceived usefulness, perceived ease of usefulness negatively influences perceived cyber threats, and perceived cyber threats negatively influence the level of trust. This research introduced a new application of the TAM and provides the automotive industry with quantifiable metrics that link cybersecurity perceptions to increasing trust in autonomous vehicles.
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538 $a Mode of access: World Wide Web
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650 4 $a Transportation. $3 555912
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