Web cookies have been the subject of many research studies over the last few years. However, most existing research does not consider multiple crucial perspectives that can influence the cookie landscape, such as the client's location, the impact of cookie banner interaction, and from which operating system a website is being visited. In this paper, we conduct a comprehensive measurement study to analyze the cookie landscape for Tranco top-10k websites from different geographic locations and analyze multiple different perspectives. One important factor which influences cookies is the use of cookie banners. We develop a tool, BannerClick, to automatically detect, accept, and reject cookie banners with an accuracy of 99%, 97%, and 87%, respectively. We find banners to be 56% more prevalent when visiting websites from within the EU region. Moreover, we analyze the effect of banner interaction on different types of cookies (i.e., first-party, third-party, and tracking). For instance, we observe that websites send, on average, 5.5x more third-party cookies after clicking ``accept'', underlining that it is critical to interact with banners when performing Web measurements. Additionally, we analyze statistical consistency, evaluate the widespread deployment of consent management platforms, compare landing to inner pages, and assess the impact of visiting a website on a desktop compared to a mobile phone. Our study highlights that all of these factors substantially impact the cookie landscape, and thus a multi-perspective approach should be taken when performing Web measurement studies.
翻译:过去几年来,许多网络饼干一直是许多研究研究的主题。然而,大多数现有研究没有考虑能够影响饼干景观的多重关键观点,例如客户位置、饼干横幅互动的影响、以及访问网站的操作系统。在本文中,我们开展了一项全面测量研究,以分析来自不同地理位置的Tranco顶层10k网站的饼干景观,并分析多种不同观点。影响饼干的一个重要因素是使用饼干横幅。我们开发了一个工具BannerClick,以自动检测、接受和拒绝精确度分别为99%、97%和87%的饼干横幅。我们发现在访问欧盟区域内的网站时,横幅比56%更加流行。此外,我们分析横幅互动对不同类型饼干(即第一党、第三党和跟踪)的影响。例如,我们观察到网站在点击“接受”之后平均发送5.5x更多的第三方饼干,强调在进行网络测量时,与横幅互动至关重要。此外,我们在访问欧盟区域的网站访问网站时,将分析统计的一致性,从而评估对不同类型(即第一党、第三党和跟踪)网站的影响。我们进行广泛应用的在线分析,评估。我们网站的影响,将评估如何评估。