User valuation of secrecy Framing based on General Data Protection Regulation (GDPR) users

J. R. Annam, Pavan Kumar Ande, Bhargavi Kanuri, C. Prasad, B. S. Babu, Poojitha Tatineni
{"title":"User valuation of secrecy Framing based on General Data Protection Regulation (GDPR) users","authors":"J. R. Annam, Pavan Kumar Ande, Bhargavi Kanuri, C. Prasad, B. S. Babu, Poojitha Tatineni","doi":"10.1109/ICIRCA51532.2021.9544896","DOIUrl":null,"url":null,"abstract":"This research paper suggests to build on the results obtained by Goldin and Reck (2020). It suggests to collect a dataset that can be used to test their method. At the same time, the results from the analysis of this dataset will produce framing-consistent estimates of users' privacy setting preferences. The test of Goldin and Reck (2020)'s method will constitute a methodological contribution to the literature on revealed preferences under framing. The preference estimates will contribute to the literature on privacy preferences and will have implications for policy makers concerned with the security concern on personal data present on the internet. It is proposed to write a similar browser add-on to track people's decision about browser cookie settings. According to the General Data Protection Regulation (GDPR) users, who visit a website from within the European Union or the European Economic Area must be asked for their stated consent on storing browser cookies (General Data Protection Regulation 2020). For the intents of this research proposal, one can divide browser cookies into two groups. First, there are essential cookies that are necessary to guarantee the website's functionality. Second, there are third-party ad-tracking cookies. A website's host still has a monetary incentive to nudge users to allow for the ad-tracking cookies. This can be done by choosing the default cookie settings.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIRCA51532.2021.9544896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This research paper suggests to build on the results obtained by Goldin and Reck (2020). It suggests to collect a dataset that can be used to test their method. At the same time, the results from the analysis of this dataset will produce framing-consistent estimates of users' privacy setting preferences. The test of Goldin and Reck (2020)'s method will constitute a methodological contribution to the literature on revealed preferences under framing. The preference estimates will contribute to the literature on privacy preferences and will have implications for policy makers concerned with the security concern on personal data present on the internet. It is proposed to write a similar browser add-on to track people's decision about browser cookie settings. According to the General Data Protection Regulation (GDPR) users, who visit a website from within the European Union or the European Economic Area must be asked for their stated consent on storing browser cookies (General Data Protection Regulation 2020). For the intents of this research proposal, one can divide browser cookies into two groups. First, there are essential cookies that are necessary to guarantee the website's functionality. Second, there are third-party ad-tracking cookies. A website's host still has a monetary incentive to nudge users to allow for the ad-tracking cookies. This can be done by choosing the default cookie settings.
基于通用数据保护条例(GDPR)用户的保密框架用户评估
本研究论文建议以Goldin和Reck(2020)获得的结果为基础。它建议收集一个数据集,可以用来测试他们的方法。同时,对该数据集的分析结果将产生与框架一致的用户隐私设置偏好估计。Goldin和Reck(2020)方法的测试将对框架下揭示偏好的文献做出方法论贡献。偏好估计将有助于有关隐私偏好的文献,并将对关注互联网上个人数据安全问题的政策制定者产生影响。有人建议编写一个类似的浏览器插件来跟踪人们对浏览器cookie设置的决定。根据《通用数据保护条例》(GDPR),从欧盟或欧洲经济区访问网站的用户必须征得他们对存储浏览器cookie的明确同意(《2020年通用数据保护条例》)。为了本研究计划的目的,可以将浏览器cookie分为两组。首先,有必要的cookie,以保证网站的功能。其次,还有第三方广告跟踪cookie。网站的主机仍然有金钱上的动机来促使用户允许广告跟踪cookie。这可以通过选择默认的cookie设置来实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信