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Searching for Privacy in an Increasingly Public World: Exploits, Experience, and Errors Toward New. Models for Access Control in Online Environments.

机译:在日益公开的世界中搜索隐私:新的漏洞,经验和错误。在线环境中的访问控制模型。

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摘要

Increasingly, more users and organizations are pushing their data into what is currently known as the "cloud." In such an environment, huge amounts of valuable data are stored and accessible almost ubiquitously within a network. As this trend continues, privacy and access control become increasingly relevant concepts to consider. Unfortunately application developers, service providers, and researchers are only just beginning to understand the challenges associated with the rapidly increasing integration of personal data into the "cloud." Also, much of what has been implemented to provide access control and privacy is based on simple and mostly manual mechanisms. While the amount of data available has grown exponentially and the uses of and services for this data rapidly evolve, the protection mechanisms for this data have changed at a significantly slower pace. This state of affairs does not bode well for those concerned about or tasked with protecting online data.;This dissertation addresses this growing challenge through the exploration of new models for privacy and access control that are based on the mental models (e.g., human and social factors) that affect privacy and access control. More specifically, this thesis represents an early attempt to understand and capture the mental processes that people use to make sharing decisions offline as input to access control mechanisms for online environments. The key contributions of this dissertation are a comprehensive exploration of the factors that affect access control in both online and offline environments, system designs and implementations for leveraging these factors for access control and privacy, and survey data and analysis collected about users, their relationships, and their sharing preferences.
机译:越来越多的用户和组织将其数据推送到当前称为“云”的位置。在这样的环境中,网络中几乎无处不在存储和访问大量有价值的数据。随着这种趋势的继续,隐私和访问控制已成为越来越重要的考虑概念。不幸的是,应用程序开发人员,服务提供商和研究人员才刚刚开始了解与将个人数据迅速集成到“云”中相关的挑战。同样,为提供访问控制和隐私而实现的许多内容都基于简单的手动机制。尽管可用数据量呈指数级增长,并且该数据的使用和服务迅速发展,但该数据的保护机制却以非常缓慢的速度变化。对于那些关心或负责保护在线数据的人们来说,这种情况并不好。;本论文通过探索基于心理模型(例如,人类和社交模型)的隐私和访问控制新模型来解决这一日益严峻的挑战。因素)会影响隐私和访问控制。更具体地说,本论文代表了一种早期的尝试,旨在理解和捕捉人们用来脱机做出共享决策的心理过程,以此作为对在线环境访问控制机制的输入。本论文的主要贡献是全面探讨了影响在线和离线环境中访问控制的因素,利用这些因素进行访问控制和隐私的系统设计和实现,以及收集了有关用户及其关系的调查数据和分析,以及他们的共享偏好。

著录项

  • 作者

    Banks, Lerone D.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Sociology Theory and Methods.;Computer Science.;Web Studies.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 100 p.
  • 总页数 100
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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