管理智能建筑中隐私悖论的知情同意模型

Chehara Pathmabandu, J. Grundy, Mohan Baruwal Chhetri, Z. Baig
{"title":"管理智能建筑中隐私悖论的知情同意模型","authors":"Chehara Pathmabandu, J. Grundy, Mohan Baruwal Chhetri, Z. Baig","doi":"10.1145/3417113.3422180","DOIUrl":null,"url":null,"abstract":"Smart Buildings are defined as the “buildings of the future” and use the latest Internet of Things (IoT) technologies to automate building operations and services. This is to both increase operational efficiency as well as maximize occupant comfort and environmental impact. However, these “smart devices” - typically used with default settings - also enable the capture and sharing of a variety of sensitive and personal data about the occupants. Given the non-intrusive nature of most IoT devices, individuals have little awareness of what data is being collected about them and what happens to it downstream. Even if they are aware, convenience overrides any privacy concerns, and they do not take sufficient steps to control the data collection, thereby exacerbating the privacy paradox. At the same time, IoT-based building automation systems are revealing highly sensitive insights about the building occupants by synthesizing data from multiple sources and this can be exploited by the device vendors and unauthorised third parties. To address the tension between privacy and convenience in an increasingly connected world, we propose a user-centric informed consent model to foster an accurate user discretion process for privacy choice in IoT-enabled smart buildings. The proposed model aims to (a) inform and increase user awareness about how their data is being collected and used, (b) provide fine-grained visibility into privacy compliance and infringement by IoT devices, and (c) recommend corrective actions through nudges (or soft notifications). We illustrate how our proposed consent model works through a use case scenario of a voice-activated smart office.","PeriodicalId":110590,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An Informed Consent Model for Managing the Privacy Paradox in Smart Buildings\",\"authors\":\"Chehara Pathmabandu, J. Grundy, Mohan Baruwal Chhetri, Z. Baig\",\"doi\":\"10.1145/3417113.3422180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart Buildings are defined as the “buildings of the future” and use the latest Internet of Things (IoT) technologies to automate building operations and services. This is to both increase operational efficiency as well as maximize occupant comfort and environmental impact. However, these “smart devices” - typically used with default settings - also enable the capture and sharing of a variety of sensitive and personal data about the occupants. Given the non-intrusive nature of most IoT devices, individuals have little awareness of what data is being collected about them and what happens to it downstream. Even if they are aware, convenience overrides any privacy concerns, and they do not take sufficient steps to control the data collection, thereby exacerbating the privacy paradox. At the same time, IoT-based building automation systems are revealing highly sensitive insights about the building occupants by synthesizing data from multiple sources and this can be exploited by the device vendors and unauthorised third parties. To address the tension between privacy and convenience in an increasingly connected world, we propose a user-centric informed consent model to foster an accurate user discretion process for privacy choice in IoT-enabled smart buildings. The proposed model aims to (a) inform and increase user awareness about how their data is being collected and used, (b) provide fine-grained visibility into privacy compliance and infringement by IoT devices, and (c) recommend corrective actions through nudges (or soft notifications). We illustrate how our proposed consent model works through a use case scenario of a voice-activated smart office.\",\"PeriodicalId\":110590,\"journal\":{\"name\":\"2020 35th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 35th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3417113.3422180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 35th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3417113.3422180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

智能建筑被定义为“未来的建筑”,并使用最新的物联网(IoT)技术来自动化建筑操作和服务。这既是为了提高运营效率,也是为了最大限度地提高乘员舒适度和对环境的影响。然而,这些通常带有默认设置的“智能设备”也可以捕获和共享有关居住者的各种敏感和个人数据。考虑到大多数物联网设备的非侵入性,个人几乎不知道正在收集关于他们的哪些数据以及在下游发生了什么。即使他们意识到这一点,便利也压倒了任何隐私问题,他们没有采取足够的措施来控制数据收集,从而加剧了隐私悖论。与此同时,基于物联网的楼宇自动化系统通过综合来自多个来源的数据,揭示了有关建筑物居住者的高度敏感的见解,这可能被设备供应商和未经授权的第三方利用。为了解决日益互联的世界中隐私和便利之间的紧张关系,我们提出了一个以用户为中心的知情同意模型,以促进在支持物联网的智能建筑中进行隐私选择的准确用户自由决定过程。提出的模型旨在(a)告知和提高用户对其数据收集和使用方式的认识,(b)对物联网设备的隐私合规性和侵权行为提供细粒度的可见性,以及(c)通过轻推(或软通知)建议纠正措施。我们通过一个声控智能办公室的用例场景来说明我们提出的同意模型是如何工作的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Informed Consent Model for Managing the Privacy Paradox in Smart Buildings
Smart Buildings are defined as the “buildings of the future” and use the latest Internet of Things (IoT) technologies to automate building operations and services. This is to both increase operational efficiency as well as maximize occupant comfort and environmental impact. However, these “smart devices” - typically used with default settings - also enable the capture and sharing of a variety of sensitive and personal data about the occupants. Given the non-intrusive nature of most IoT devices, individuals have little awareness of what data is being collected about them and what happens to it downstream. Even if they are aware, convenience overrides any privacy concerns, and they do not take sufficient steps to control the data collection, thereby exacerbating the privacy paradox. At the same time, IoT-based building automation systems are revealing highly sensitive insights about the building occupants by synthesizing data from multiple sources and this can be exploited by the device vendors and unauthorised third parties. To address the tension between privacy and convenience in an increasingly connected world, we propose a user-centric informed consent model to foster an accurate user discretion process for privacy choice in IoT-enabled smart buildings. The proposed model aims to (a) inform and increase user awareness about how their data is being collected and used, (b) provide fine-grained visibility into privacy compliance and infringement by IoT devices, and (c) recommend corrective actions through nudges (or soft notifications). We illustrate how our proposed consent model works through a use case scenario of a voice-activated smart office.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信