Towards Classifying Third-Party Web Services at Scale

Many people are concerned about privacy in the Web. This has resulted in the emergence of various tools and sugges-tions for blocking tracking services. However, in order to block or analyze tracking services, these services have to be identified first. In this work we develop and evaluate a set of features for identifying tracking services in HTTP traffic. Our approach enables us to verify the effectiveness of exist-ing blocking approaches as well as to find more candidates for blacklisting