Third-party services form an integral part of the mobile ecosystem: they ease application development and enable features such as analytics, social network integration, and app monetization through ads. However, aided by the general opacity of mobile systems, such services are also largely invisible to users. This has negative consequences for user privacy as third-party services can potentially track users without their consent, even across multiple applications. Using real-world mobile traffic data gathered by the Lumen Privacy Monitor (Lumen), a privacyenhancing app with the ability to analyze network traffic on mobile devices in user space, we present insights into the mobile advertising and tracking ecosystem and its stakeholders. In this study, we develop automated methods to detect third-party advertising and tracking services at the traffic level. Using this technique we identify 2,121 such services, of which 233 were previously unknown to other popular advertising and tracking blacklists. We then uncover the business relationships between the providers of these services and characterize them by their prevalence in the mobile and Web ecosystem. Our analysis of the privacy policies of the largest advertising and tracking service providers shows that sharing harvested data with subsidiaries and third-party affiliates is the norm. Finally, we seek to identify the services likely to be most impacted by privacy regulations such as the European General Data Protection Regulation (GDPR) and ePrivacy directives.

We present the first study of network access link performance measured directly from home gateway devices. Policymakers, ISPs, and users are increasingly interested in studying the performance of Internet access links. Because of many confounding factors in a home network or on end hosts, however, thoroughly understanding access network performance requires deploying measurement infrastructure in users' homes as gateway devices. In conjunction with the Federal Communication Commission's study of broadband Internet access in the United States, we study the throughput and latency of network access links using longitudinal measurements from nearly 4,000 gateway devices across 8 ISPs from a deployment of over 4,200 devices. We study the performance users achieve and how various factors ranging from the user's choice of modem to the ISP's traffic shaping policies can affect performance. Our study yields many important findings about the characteristics of existing access networks. Our findings also provide insights into the ways that access network performance should be measured and presented to users, which can help inform ongoing broader efforts to benchmark the performance of access networks.

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We measure Web performance bottlenecks in home broadband access networks and evaluate ways to mitigate these bottlenecks with caching within home networks. We first measure Web performance bottlenecks to nine popular Web sites from more than 5,000 broadband access networks and demonstrate that when the downstream throughput of the access link exceeds about 16 Mbits/s, latency is the main bottleneck for Web page load time. Next, we use a routerbased Web measurement tool, Mirage, to deconstruct Web page load time into its constituent components (DNS lookup, TCP connection setup, object download) and show that simple latency optimizations can yield significant improvements in overall page load times. We then present a case for placing a cache in the home network and deploy three common optimizations: DNS caching, TCP connection caching, and content caching. We show that caching only DNS and TCP connections yields significant improvements in page load time, even when the user's browser is already performing similar independent optimizations. Finally, we use traces from real homes to demonstrate how prefetching DNS and TCP connections for popular sites in a home-router cache can achieve faster page load times.

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