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: 1640664
• 负责人: Bart Knijnenburg
• 金额: $ 17.55万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1640664&HistoricalAwards=false
• 关键词: EAGER; Collaborative; PRICE; Using; process

Household Internet-of-Things (IoT) devices are intended to collect information in the home and to communicate with each other, to create powerful new applications that support our day-to-day activities. Existing research suggests that users have a difficult time selecting their privacy settings on such devices. The goal of this project is to investigate how, why and when privacy decisions of household IoT users are suboptimal, and to use the insights from this research to create and test a simple single user interface that integrates privacy settings across all devices within a household. This interface will have a flexible set of privacy profiles that fits a wide range of privacy preferences and also helps US companies to comply with EU privacy regulations when they operate in the European market.Unlike existing privacy research, which assumes that users employ limited but essentially rational decision-making practices, this project aims to understand consumers' actual decision processes. In this way we can improve theories about privacy decision making using part-worth utility mapping and process tracing (including eye-tracking). The results of these efforts are used to develop a data-driven set of privacy profiles that cover the privacy preferences of most users. These profiles are then integrated into a privacy management interface (an open-source contribution to an existing IoT management platform) that does not overload users with information and control, but instead leverages their existing decision processes and avoids their biases.

家用物联网（IoT）设备旨在收集家中的信息并相互通信，以创建支持我们日常活动的强大新应用程序。现有的研究表明，用户很难在这些设备上选择他们的隐私设置。该项目的目标是调查家庭物联网用户的隐私决策是如何，为什么以及何时是次优的，并利用这项研究的见解来创建和测试一个简单的单一用户界面，该界面集成了家庭中所有设备的隐私设置。这个界面将有一套灵活的隐私配置文件，适合广泛的隐私偏好，也有助于美国公司在欧洲市场运营时遵守欧盟隐私法规。与现有的隐私研究不同，现有的隐私研究假设用户采用有限但基本上理性的决策实践，该项目旨在了解消费者的实际决策过程。 通过这种方式，我们可以使用部分价值效用映射和过程跟踪（包括眼动跟踪）来改进隐私决策理论。这些努力的结果用于开发一组数据驱动的隐私配置文件，涵盖大多数用户的隐私偏好。然后，这些配置文件被集成到隐私管理界面（对现有物联网管理平台的开源贡献）中，该界面不会使用户的信息和控制过载，而是利用他们现有的决策过程并避免他们的偏见。

项目成果

A recommendation approach for user privacy preferences in the fitness domain

• DOI: 10.1007/s11257-019-09246-3
• 发表时间: 2019-10-12
• 期刊: USER MODELING AND USER-ADAPTED INTERACTION
• 影响因子: 3.6
• 作者: Sanchez, Odnan Ref;Torre, Ilaria;Knijnenburg, Bart P.
• 通讯作者: Knijnenburg, Bart P.

A Data-Driven Approach to Designing for Privacy in Household IoT

• DOI: 10.1145/3241378
• 发表时间: 2019-09
• 期刊: ACM Transactions on Interactive Intelligent Systems (TiiS)
• 作者: Yangyang He;Paritosh Bahirat;Bart P. Knijnenburg;A. Menon

IUIoT: intelligent user interfaces for IoT

IUIoT：物联网智能用户界面

• DOI: 10.1145/3308557.3313121
• 发表时间: 2019
• 期刊: Proceedings of the 24th International Conference on Intelligent User Interfaces: Companio
• 作者: Knijnenburg, Bart;Bahirat, Paritosh;He, Yangyang;Willemsen, Martijn;Sun, Qizhang;Kobsa, Alfred
• 通讯作者: Kobsa, Alfred

A Data-Driven Approach to Developing IoT Privacy-Setting Interfaces

开发物联网隐私设置接口的数据驱动方法

• DOI: 10.1145/3172944.3172982
• 发表时间: 2018
• 期刊: 23rd International Conference on Intelligent User Interfaces
• 作者: Bahirat, Paritosh;He, Yangyang;Menon, Abhilash;Knijnenburg, Bart
• 通讯作者: Knijnenburg, Bart

Semantic-based privacy settings negotiation and management

基于语义的隐私设置协商和管理

• DOI: 10.1016/j.future.2019.10.024
• 发表时间: 2019
• 期刊: Future Generation Computer Systems
• 作者: Sanchez, Odnan Ref;Torre, Ilaria;Knijnenburg, Bart P.
• 通讯作者: Knijnenburg, Bart P.