TrackAdvisor: Taking Back Browsing Privacy from Third-Party Trackers

Abstract

Even though most web users assume that only the websites that they visit directly become aware of the visit, this belief is incorrect. Many website display contents hosted externally by third-party websites, which can track users and become aware of their web-surfing behavior. This phenomenon is called third-party tracking, and although such activities violate no law, they raise privacy concerns because the tracking is carried out without users’ knowledge or explicit approval. Our work provides a systematic study of the third-party tracking phenomenon. First, we develop TrackAdvisor, arguably the first method that utilizes Machine Learning to identify the HTTP requests carrying sensitive information to third-party trackers with very high accuracy (100 % Recall and 99.4 Precision). Microsoft’s Tracking Protection Lists, which is a widely-used third-party tracking blacklist achieves only a Recall of 72.2 %. Second, we quantify the pervasiveness of the third-party tracking phenomenon: 46 % of the home pages of the websites in Alexa Global Top 10,000 have at least one third-party tracker, and Google, using third-party tracking, monitors 25 % of these popular websites. Our overarching goal is to measure accurately how widespread third-party tracking is and hopefully would raise the public awareness to its potential privacy risks.