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.