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TWC SBES: Medium: Collaborative: Crowdsourcing Security

TWC SBES: Medium: Collaborative: Crowdsourcing Security
TWC SBES:媒介:协作:众包安全
批准号:
1228471
负责人:
Michael Reiter
金额:
$12.22万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-01 至 2015-08-31

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中文摘要
翻译
对于大多数人来说,以确保功能、安全性和便利性之间的适当平衡的方式维护系统和设备的安全仍然很复杂。例如,系统经常询问人们是否接受安全证书、安装应用程序、注意安全警告或重新配置操作系统安全设置。虽然这些例子代表了人们经常发现自己的情况,但人们很少有任何基础来做出明智的决定或方便地建立一个决定。这项研究探讨了“众包安全”的概念,其中解决方案在于人们利用他们的社区成员来保护他们的系统和设备。本研究的主要目标是确定众包作为增强安全性的补充策略的潜力。这项研究中涉及的一个挑战与个人数据的安全有关。具体地说,这项研究试图开发一种安全机制,这种机制可以利用自然产生的社会关系,并利用“人类计算”将通过身份验证的安全负担从机器转移到人类身上。在这个框架内,该研究既调查了关于众包安全解决方案的技术有效性的问题,也调查了关于用户偏好、动机和对此类系统的隐私担忧的社会行为问题。这项研究将使社会更深入地了解如何通过人类参与和协作来更好地保护系统,从而超越当前安全机制的现状。
英文摘要
Maintaining the security of one's systems and devices in a way that ensures the right balance between functionality, security, and convenience remains complicated for most people. For example, people are routinely asked by their systems whether to accept a security certificate, install an application, heed security warnings, or reconfigure operating-system security settings. While these examples represent situations in which people regularly find themselves, people rarely have any basis to make an informed decision or to establish one conveniently. This research examines the concept of 'crowdsourced security' where the solution lies in people leveraging members of their community to secure their systems and devices.The primary goal of this research is to determine the potential of crowdsourcing as a complementary strategy for enhancing security. An example challenge addressed in this research pertains to the security of one's personal data. Specifically the research seeks to develop security mechanisms that can exploit naturally occurring social relationships and utilize 'human computation' to shift the burden of security via authentication from machines to humans. Within this framework, the research investigates both questions about the technical effectiveness of crowdsourced security solutions, as well as socio-behavioral questions about users' preferences, motivations, and privacy concerns about such systems. This research will benefit society by producing a deeper understanding of how systems can be better secured through human participation and collaboration, moving beyond the status quo of current security mechanisms.
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Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
  • 批准号:
    2338302
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $27.89万
  • 财政年份:
    2024
  • 负责人:
    Michael Reiter
  • 依托单位:
Collaborative Proposal: SaTC: Frontiers: Center for Distributed Confidential Computing (CDCC)
  • 批准号:
    2207214
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2022
  • 负责人:
    Michael Reiter
  • 依托单位:
Collaborative Research: Conference: 2022 Secure and Trustworthy Cyberspace PI Meeting
  • 批准号:
    2205940
  • 项目类别:
    Standard Grant
  • 资助金额:
    $9.16万
  • 财政年份:
    2022
  • 负责人:
    Michael Reiter
  • 依托单位:
SaTC: CORE: Medium: Collaborative: Using Machine Learning to Build More Resilient and Transparent Computer Systems
  • 批准号:
    2113345
  • 项目类别:
    Standard Grant
  • 资助金额:
    $33.33万
  • 财政年份:
    2021
  • 负责人:
    Michael Reiter
  • 依托单位:
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