论文标题
Alexa Echo智能扬声器生态系统中的跟踪，分析和广告定位
Tracking, Profiling, and Ad Targeting in the Alexa Echo Smart Speaker Ecosystem
论文作者
论文摘要
智能扬声器收集语音命令，可用于推断有关用户的敏感信息。鉴于潜在的隐私危害，需要更高的透明度和控制智能扬声器平台收集，使用和共享的数据以及支持其支持的第三方技能。为了弥合这一差距，我们建立了一个框架，以测量智能扬声器平台的数据收集，使用和共享。我们将框架应用于亚马逊智能扬声器生态系统。我们的结果表明，亚马逊和第三方，包括智能扬声器生态系统独有的广告和跟踪服务，收集智能扬声器交互数据。我们还发现，亚马逊处理智能扬声器交互数据以推断用户兴趣，并使用这些推论将有针对性的广告提供给用户。智能扬声器的互动还导致广告定位，并且来自第三方广告商的广告拍卖中的出价高达30倍。最后，我们发现亚马逊和第三方技能的数据实践通常在其政策文件中没有清楚地披露。
Smart speakers collect voice commands, which can be used to infer sensitive information about users. Given the potential for privacy harms, there is a need for greater transparency and control over the data collected, used, and shared by smart speaker platforms as well as third party skills supported on them. To bridge this gap, we build a framework to measure data collection, usage, and sharing by the smart speaker platforms. We apply our framework to the Amazon smart speaker ecosystem. Our results show that Amazon and third parties, including advertising and tracking services that are unique to the smart speaker ecosystem, collect smart speaker interaction data. We also find that Amazon processes smart speaker interaction data to infer user interests and uses those inferences to serve targeted ads to users. Smart speaker interaction also leads to ad targeting and as much as 30X higher bids in ad auctions, from third party advertisers. Finally, we find that Amazon's and third party skills' data practices are often not clearly disclosed in their policy documents.
