Meta 上的客户端和服务器端跟踪:有效性和准确性

Asmaa El fraihi, Nardjes Amieur, Walter Rudametkin, Oana Goga
{"title":"Meta 上的客户端和服务器端跟踪:有效性和准确性","authors":"Asmaa El fraihi, Nardjes Amieur, Walter Rudametkin, Oana Goga","doi":"10.56553/popets-2024-0086","DOIUrl":null,"url":null,"abstract":"Growing concern over digital privacy has led to the widespread use of tracking restriction tools, such as ad blockers, Virtual Private Networks (VPN), and privacy-focused web browsers. All major browser vendors have also deprecated, or plan to deprecate, third-party cookies to reduce tracking. Despite these efforts, advertising companies continuously innovate to overcome these restrictions. Recently, advertising platforms, like Meta, have been promoting server-side tracking solutions to bypass traditional browser-based tracking restrictions.\nThis paper explores how server-side tracking technologies can link website visitors with their user accounts on Meta products. The goal is to assess the effectiveness and accuracy of employing this technology, as well as the effect of tracking restrictions on online tracking. Our methodology involves a series of experiments where we integrate Meta's client-side tracker (the Meta Pixel) and server-side technology (the Conversions API) on different web pages. We then drive traffic to these pages and evaluate the success rate of linking website visitors to their profiles on Meta products.\nOur findings show that Meta's server-side technology can match between 34% and 51% of website visitors to user profiles on Meta products using basic information like the visitor's IP address, user agent, and location data. This is comparable to Pixel-based user matching in optimal conditions (i.e., in the absence of tracking restrictions), which links between 42% and 61% of user profiles. Nevertheless, we see a considerable difference in accuracy: while the Pixel-based tracking achieves 100% accuracy, less than 65% of the profiles matched by server-side tracking are accurate.","PeriodicalId":519525,"journal":{"name":"Proceedings on Privacy Enhancing Technologies","volume":"17 24","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Client-side and Server-side Tracking on Meta: Effectiveness and Accuracy\",\"authors\":\"Asmaa El fraihi, Nardjes Amieur, Walter Rudametkin, Oana Goga\",\"doi\":\"10.56553/popets-2024-0086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Growing concern over digital privacy has led to the widespread use of tracking restriction tools, such as ad blockers, Virtual Private Networks (VPN), and privacy-focused web browsers. All major browser vendors have also deprecated, or plan to deprecate, third-party cookies to reduce tracking. Despite these efforts, advertising companies continuously innovate to overcome these restrictions. Recently, advertising platforms, like Meta, have been promoting server-side tracking solutions to bypass traditional browser-based tracking restrictions.\\nThis paper explores how server-side tracking technologies can link website visitors with their user accounts on Meta products. The goal is to assess the effectiveness and accuracy of employing this technology, as well as the effect of tracking restrictions on online tracking. Our methodology involves a series of experiments where we integrate Meta's client-side tracker (the Meta Pixel) and server-side technology (the Conversions API) on different web pages. We then drive traffic to these pages and evaluate the success rate of linking website visitors to their profiles on Meta products.\\nOur findings show that Meta's server-side technology can match between 34% and 51% of website visitors to user profiles on Meta products using basic information like the visitor's IP address, user agent, and location data. This is comparable to Pixel-based user matching in optimal conditions (i.e., in the absence of tracking restrictions), which links between 42% and 61% of user profiles. Nevertheless, we see a considerable difference in accuracy: while the Pixel-based tracking achieves 100% accuracy, less than 65% of the profiles matched by server-side tracking are accurate.\",\"PeriodicalId\":519525,\"journal\":{\"name\":\"Proceedings on Privacy Enhancing Technologies\",\"volume\":\"17 24\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings on Privacy Enhancing Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56553/popets-2024-0086\",\"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 on Privacy Enhancing Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56553/popets-2024-0086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人们对数字隐私的关注与日俱增,导致追踪限制工具的广泛使用,如广告拦截器、虚拟专用网络(VPN)和注重隐私的网络浏览器。所有主要的浏览器供应商也都已废弃或计划废弃第三方 cookie,以减少跟踪。尽管做出了这些努力,广告公司仍在不断创新,以克服这些限制。最近,Meta 等广告平台一直在推广服务器端跟踪解决方案,以绕过传统的基于浏览器的跟踪限制。本文探讨了服务器端跟踪技术如何将网站访问者与其在 Meta 产品上的用户账户联系起来。本文探讨了服务器端跟踪技术如何将网站访问者与其在 Meta 产品上的用户账户联系起来,目的是评估采用这种技术的有效性和准确性,以及跟踪限制对在线跟踪的影响。我们的方法包括一系列实验,在不同的网页上集成 Meta 的客户端跟踪器(Meta Pixel)和服务器端技术(Conversions API)。我们的研究结果表明,Meta 的服务器端技术可以利用访问者的 IP 地址、用户代理和位置数据等基本信息,将 34% 到 51% 的网站访问者与 Meta 产品上的用户配置文件进行匹配。这与在最佳条件下(即在没有跟踪限制的情况下)基于像素的用户匹配效果相当,后者能链接 42% 到 61% 的用户资料。尽管如此,我们还是看到了准确率上的巨大差异:基于像素的跟踪达到了 100%的准确率,而通过服务器端跟踪匹配的配置文件准确率不到 65%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Client-side and Server-side Tracking on Meta: Effectiveness and Accuracy
Growing concern over digital privacy has led to the widespread use of tracking restriction tools, such as ad blockers, Virtual Private Networks (VPN), and privacy-focused web browsers. All major browser vendors have also deprecated, or plan to deprecate, third-party cookies to reduce tracking. Despite these efforts, advertising companies continuously innovate to overcome these restrictions. Recently, advertising platforms, like Meta, have been promoting server-side tracking solutions to bypass traditional browser-based tracking restrictions. This paper explores how server-side tracking technologies can link website visitors with their user accounts on Meta products. The goal is to assess the effectiveness and accuracy of employing this technology, as well as the effect of tracking restrictions on online tracking. Our methodology involves a series of experiments where we integrate Meta's client-side tracker (the Meta Pixel) and server-side technology (the Conversions API) on different web pages. We then drive traffic to these pages and evaluate the success rate of linking website visitors to their profiles on Meta products. Our findings show that Meta's server-side technology can match between 34% and 51% of website visitors to user profiles on Meta products using basic information like the visitor's IP address, user agent, and location data. This is comparable to Pixel-based user matching in optimal conditions (i.e., in the absence of tracking restrictions), which links between 42% and 61% of user profiles. Nevertheless, we see a considerable difference in accuracy: while the Pixel-based tracking achieves 100% accuracy, less than 65% of the profiles matched by server-side tracking are accurate.
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