揭示生物识别特征对用户安全行为的并列影响:有争议的信息技术视角

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jing Zhang , Zilong Liu , Xin (Robert) Luo
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引用次数: 0

摘要

生物识别身份验证已经无处不在,并对个人和企业的决策产生了深远影响。尽管生物识别技术得到了广泛应用,但在理解生物识别特征对用户安全行为的细微影响方面仍存在明显的知识差距。为了推进这一研究方向,我们采用了有争议的信息技术框架,深入研究生物识别特征的并列性质,即生物识别特征同时带来好处和担忧,对用户的转换行为产生相反的影响。我们采用了一种有序的混合方法,首先进行了半结构式访谈,发现了三种关键的生物识别特征,并确定了与之相关的两种好处和两种担忧。我们还进行了一项后续调查,以探讨每个已识别特征之间的相互作用。结果强调了生物识别特征在塑造用户安全行为方面的关键作用。我们的研究从有争议的信息技术角度审视了用户在生物识别身份验证方面的行为,为理论理解做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unraveling juxtaposed effects of biometric characteristics on user security behaviors: A controversial information technology perspective

Biometric authentication has become ubiquitous and profoundly impacts decision-making for both individuals and firms. Despite its extensive implementation, there is a discernible knowledge gap in understanding the nuanced influence of biometric characteristics on user security behaviors. To advance this line of research, we embrace the controversial information technology framework to delve into the juxtaposed nature of biometric characteristics, wherein they concurrently yield benefits and raise concerns that manifest in opposing effects on users' switching behavior. Adopting a sequential mixed methods approach, we first conducted semi-structured interviews that uncovered three key biometric characteristics and identified two benefits and two concerns associated with them. A follow-up survey was conducted to explore the interplay between each identified construct. The results emphasize the pivotal role of biometric characteristics in shaping user security behavior. Our research contributes to theoretical understanding by scrutinizing user behaviors vis-à-vis biometric authentication through a controversial IT perspective.

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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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