Abstract: Real-Time Bidding is a novel channel of serving content (such as ads) to Web users. Programmatic ad buying is a growing trend, and billions of dollars are devoted to digital ads displaying using this technology. We analyze this technology from privacy, transparency and security point of views. We present a privacy and transparency enhancing tool showing to users when RTB ads are displayed on a visited Web site and how much is paid by advertisers. Using this tool we obtain a significant dataset of RTB winning bids (17,289 bids with an average value of $0.0012) from real, highly profiled users; we detect about 70 bidders. We discuss a design characteristic of RTB systems allowing to observe the prices which advertisers pay for serving ads to Web users. We leverage this feature (information leak of business logic) and provide insights into these prices. We show the variations of prices according to context information (such as user’s location). On the user-submitted data, we confirm that profiled users (with known Web browsing history) are evaluated higher than new comers and that some user profiles are more valuable than others. We conclude with a discussion of security aspects and consequences of RTB’s design.
This event is hosted by the IEEE CS/SMCS Austria Chapter.