As Internet streaming of live content has gained on traditional cable TV viewership, we have also seen significant growth of free live streaming services which illegally provide free access to copyrighted content over the Internet. Some of these services draw millions of viewers each month. Moreover, this viewership has continued to increase, despite the consistent coupling of this free content with deceptive advertisements and user-hostile tracking. In this paper, we explore the ecosystem of free illegal live streaming services by collecting and examining the behavior of a large corpus of illegal sports streaming websites. We explore and quantify evidence of user tracking via third-party HTTP requests, cookies, and fingerprinting techniques on more than @math unique video streams provided by @math unique illegal live streaming domains. We compare the behavior of illegal live streaming services with legitimate services and find that the illegal services go to much greater lengths to track users than most legitimate services, and use more obscure tracking services. Similarly, we find that moderated sites that aggregate links to illegal live streaming content fail to moderate out sites that go to significant lengths to track users. In addition, we perform several case studies which highlight deceptive behavior and modern techniques used by some domains to avoid detection, monetize traffic, or otherwise exploit their viewers. Overall, we find that despite recent improvements in mechanisms for detecting malicious browser extensions, ad-blocking, and browser warnings, users of free illegal live streaming services are still exposed to deceptive ads, malicious browser extensions, scams, and extensive tracking. We conclude with insights into the ecosystem and recommendations for addressing the challenges highlighted by this study.
Third-party networks collect vast amounts of data about users via websites and mobile applications. Consolidations among tracker companies can significantly increase their individual tracking capabilities, prompting scrutiny by competition regulators. Traditional measures of market share, based on revenue or sales, fail to represent the tracking capability of a tracker, especially if it spans both web and mobile. This article proposes a new approach to measure the concentration of tracking capability, based on the reach of a tracker on popular websites and apps. Our results reveal that tracker prominence and parent–subsidiary relationships have significant impact on accurately measuring concentration. We present the largest and most detailed measurement of online tracking conducted to date, based on a crawl of the top 1 million websites. We make 15 types of measurements on each site, including stateful (cookie-based) and stateless (fingerprinting-based) tracking, the effect of browser privacy tools, and the exchange of tracking data between different sites ("cookie syncing"). Our findings include multiple sophisticated fingerprinting techniques never before measured in the wild. This measurement is made possible by our open-source web privacy measurement tool, OpenWPM, which uses an automated version of a full-fledged consumer browser. It supports parallelism for speed and scale, automatic recovery from failures of the underlying browser, and comprehensive browser instrumentation. We demonstrate our platform's strength in enabling researchers to rapidly detect, quantify, and characterize emerging online tracking behaviors. Different countries have different privacy regulatory models. These models impact the perspectives and laws surrounding internet privacy. However, little is known about how effective the regulatory models are when it comes to limiting online tracking and advertising activity. In this paper, we propose a method for investigating tracking behavior by analyzing cookies and HTTP requests from browsing sessions originating in different countries. We collect browsing data from visits to top websites in various countries that utilize different regulatory models. We found that there are significant differences in tracking activity between different countries using several metrics. We also suggest various ways to extend this study which may yield a more complete representation of tracking from a global perspective.