选择退出真的能让我退出吗?

D. Bui, Brian Tang, K. Shin
{"title":"选择退出真的能让我退出吗?","authors":"D. Bui, Brian Tang, K. Shin","doi":"10.1145/3548606.3560574","DOIUrl":null,"url":null,"abstract":"Online trackers, such as advertising and analytics services, have provided users with choices to opt out of their tracking and data collection to mitigate the users' concerns about increased privacy risks. While opt-out choices of online services for the cookies placed on their own websites have been examined before, the choices provided by trackers for their third-party tracking services on publisher websites have been largely overlooked. There is no guarantee that a tracker's opt-out options would faithfully follow the statements in its privacy policy. To address this concern, we develop an automated framework, called OptOutCheck, that analyzes (in)consistencies between trackers' data practices and the opt-out choice statements in their privacy policies. We create sentence-level classifiers, which achieve ≥ 84.6% precision on previously-unseen statements, to extract the opt-out policies that state neither tracking nor data collection for opted-out users from trackers' privacy-policy documents. tOptOutCheck analyzes both tracker and publisher websites to detect opt-out buttons, perform the opt-out, and extract the data flows to the tracker servers after the user opts out. Finally, we formalize the opt-out policies and data flows to derive logical conditions to detect the inconsistencies. In a large-scale study of 2.9k popular trackers, OptOutCheck detected opt-out choices on 165 trackers and found 11 trackers who exhibited data practices inconsistent with their stated opt-out policies. Since inconsistencies are violations of the trackers' privacy policies and demonstrate data collection without user consent, they are likely to lose users' trust in the online trackers and trigger the necessity of an automatic auditing process.","PeriodicalId":435197,"journal":{"name":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","volume":"150 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Do Opt-Outs Really Opt Me Out?\",\"authors\":\"D. Bui, Brian Tang, K. Shin\",\"doi\":\"10.1145/3548606.3560574\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online trackers, such as advertising and analytics services, have provided users with choices to opt out of their tracking and data collection to mitigate the users' concerns about increased privacy risks. While opt-out choices of online services for the cookies placed on their own websites have been examined before, the choices provided by trackers for their third-party tracking services on publisher websites have been largely overlooked. There is no guarantee that a tracker's opt-out options would faithfully follow the statements in its privacy policy. To address this concern, we develop an automated framework, called OptOutCheck, that analyzes (in)consistencies between trackers' data practices and the opt-out choice statements in their privacy policies. We create sentence-level classifiers, which achieve ≥ 84.6% precision on previously-unseen statements, to extract the opt-out policies that state neither tracking nor data collection for opted-out users from trackers' privacy-policy documents. tOptOutCheck analyzes both tracker and publisher websites to detect opt-out buttons, perform the opt-out, and extract the data flows to the tracker servers after the user opts out. Finally, we formalize the opt-out policies and data flows to derive logical conditions to detect the inconsistencies. In a large-scale study of 2.9k popular trackers, OptOutCheck detected opt-out choices on 165 trackers and found 11 trackers who exhibited data practices inconsistent with their stated opt-out policies. Since inconsistencies are violations of the trackers' privacy policies and demonstrate data collection without user consent, they are likely to lose users' trust in the online trackers and trigger the necessity of an automatic auditing process.\",\"PeriodicalId\":435197,\"journal\":{\"name\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"volume\":\"150 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3548606.3560574\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3548606.3560574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在线跟踪器,如广告和分析服务,为用户提供了退出跟踪和数据收集的选择,以减轻用户对隐私风险增加的担忧。虽然以前已经审查了在线服务对放置在自己网站上的cookie的选择,但跟踪器为出版商网站上的第三方跟踪服务提供的选择在很大程度上被忽视了。不能保证跟踪器的退出选项会忠实地遵循其隐私政策中的声明。为了解决这个问题,我们开发了一个名为OptOutCheck的自动化框架,用于分析追踪者的数据实践与其隐私政策中选择退出选项声明之间的一致性。我们创建了句子级分类器,对以前未见过的语句达到≥84.6%的精度,从跟踪器的隐私政策文档中提取选择退出策略,该策略既不跟踪也不收集选择退出用户的数据。tOptOutCheck分析跟踪器和发布者网站,以检测选择退出按钮,执行选择退出,并在用户选择退出后将数据流提取到跟踪器服务器。最后,我们将选择退出策略和数据流形式化,以派生出检测不一致性的逻辑条件。OptOutCheck对2.9万款流行追踪器进行了大规模研究,发现165款追踪器的选择退出选项,并发现11款追踪器的数据实践与其声明的选择退出政策不一致。由于不一致违反了跟踪器的隐私政策,表明数据收集未经用户同意,它们可能会失去用户对在线跟踪器的信任,并触发自动审计过程的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Do Opt-Outs Really Opt Me Out?
Online trackers, such as advertising and analytics services, have provided users with choices to opt out of their tracking and data collection to mitigate the users' concerns about increased privacy risks. While opt-out choices of online services for the cookies placed on their own websites have been examined before, the choices provided by trackers for their third-party tracking services on publisher websites have been largely overlooked. There is no guarantee that a tracker's opt-out options would faithfully follow the statements in its privacy policy. To address this concern, we develop an automated framework, called OptOutCheck, that analyzes (in)consistencies between trackers' data practices and the opt-out choice statements in their privacy policies. We create sentence-level classifiers, which achieve ≥ 84.6% precision on previously-unseen statements, to extract the opt-out policies that state neither tracking nor data collection for opted-out users from trackers' privacy-policy documents. tOptOutCheck analyzes both tracker and publisher websites to detect opt-out buttons, perform the opt-out, and extract the data flows to the tracker servers after the user opts out. Finally, we formalize the opt-out policies and data flows to derive logical conditions to detect the inconsistencies. In a large-scale study of 2.9k popular trackers, OptOutCheck detected opt-out choices on 165 trackers and found 11 trackers who exhibited data practices inconsistent with their stated opt-out policies. Since inconsistencies are violations of the trackers' privacy policies and demonstrate data collection without user consent, they are likely to lose users' trust in the online trackers and trigger the necessity of an automatic auditing process.
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:481959085
Book学术官方微信