EAGER: Unattended/Automated Studies of Effects of Auditory Distractions on Users Performing Security-Critical Tasks

EAGER:无人值守/自动化研究听觉干扰对执行安全关键任务的用户的影响

基本信息

  • 批准号:
    1544373
  • 负责人:
  • 金额:
    $ 23.96万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-09-01 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

User errors or delays while performing security-critical tasks can lead to undesirable or even disastrous consequences. The impact of both accidental and intentional distractions on users in such situations has received little investigation. In particular, it is unclear whether and how sensory stimuli (e.g., sound or light) influence users' behavior and trigger mistakes. Better understanding of the effects of such distractions can lead to increased user awareness and countermeasures. Preliminary studies suggest somewhat surprising effects of auditory distractions; this project develops an unattended study allowing more rigorous evaluation of the impact of distractions.The project conducts controlled user studies to examine the effects of different sound variations on participants' speed and accuracy when logging into a computer network, controlling for participants' awareness of the distraction event. Existing theory suggests auditory distractions can both improve and degrade performance; this will be carefully evaluated to determine how various stimuli impact security actions. The experiments will be conducted in a fully automated manner, which makes large-scale studies feasible and also avoids any potential experimenter bias.
用户在执行安全关键任务时的错误或延迟可能会导致不良甚至灾难性的后果。在这种情况下,意外和故意分心对用户的影响很少受到调查。 特别是,目前还不清楚感官刺激(例如,声音或光)影响用户的行为并引发错误。更好地理解这些干扰的影响可以提高用户的意识和对策。 初步研究表明,听觉干扰的影响有些令人惊讶;该项目开发了一项无人值守的研究,可以更严格地评估干扰的影响。该项目进行了受控用户研究,以检查不同声音变化对参与者登录计算机网络时的速度和准确性的影响,控制参与者对干扰事件的意识。现有的理论表明,听觉干扰可以提高和降低性能,这将被仔细评估,以确定各种刺激如何影响安全行动。 这些实验将以全自动化的方式进行,这使得大规模研究变得可行,也避免了任何潜在的实验者偏见。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Alfred Kobsa其他文献

Workshop on Adaptivity and User Modeling in Interactive Software Systems
A PLA-based privacy-enhancing user modeling framework and its evaluation
Benutzermodellierung in Dialogsystemen
对话系统中的建模
  • DOI:
    10.1007/978-3-642-70867-1
  • 发表时间:
    1985
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alfred Kobsa
  • 通讯作者:
    Alfred Kobsa
Antecedents of collective privacy management in social network sites: a cross-country analysis

Alfred Kobsa的其他文献

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{{ truncateString('Alfred Kobsa', 18)}}的其他基金

EAGER: Collaborative: PRICE: Using process tracing to improve household IoT users' privacy decisions
EAGER:协作:PRICE:使用流程跟踪来改善家庭物联网用户的隐私决策
  • 批准号:
    1640527
  • 财政年份:
    2016
  • 资助金额:
    $ 23.96万
  • 项目类别:
    Standard Grant
TWC SBE: TTP Option: Small: A User-Tailored Approach to Privacy Decision Support
TWC SBE:TTP 选项:小型:用户定制的隐私决策支持方法
  • 批准号:
    1423629
  • 财政年份:
    2014
  • 资助金额:
    $ 23.96万
  • 项目类别:
    Standard Grant
Privacy-Enabling Design of Personalized Websites
个性化网站的隐私保护设计
  • 批准号:
    0308277
  • 财政年份:
    2003
  • 资助金额:
    $ 23.96万
  • 项目类别:
    Continuing Grant

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