Today we present an updated version of our paper examining how the ubiquitous use of online tracking cookies can allow an adversary conducting network surveillance to target a user or surveil users en masse. In the initial version of the study, summarized below, we examined the technical feasibility of the attack. Now we’ve made the attack model more complete and nuanced as well as analyzed the effectiveness of several browser privacy tools in preventing the attack. Finally, inspired by Jonathan Mayer and Ed Felten’s The Web is Flat study, we incorporate the geographic topology of the Internet into our measurements of simulated web traffic and our adversary model, providing a more realistic view of how effective this attack is in practice. [Read more…]
[Steven Englehardt is a first-year Ph.D. student in the computer security group at Princeton. In this post he talks about the implications of a recent study that we published in collaboration with researchers at KU Leuven, Belgium. — Arvind Narayanan]
Online tracking is becoming more sophisticated and thus increasingly difficult to block. Modern browsers expose many surfaces that enable users to be uniquely identified, including Flash cookies and browser fingerprints. In a new paper that will appear at ACM CCS, we present the first large scale study of three advanced tracking mechanisms — canvas fingerprinting, evercookies, and cookie syncing. We developed novel measurement techniques and found that these tracking mechanisms are used on a large number of sites. Our findings on canvas fingerprinting, in particular, have been in the news (Propublica, BBC, EFF).
In this blog post I’ll focus on a different part of our paper that looked at cookie syncing, the process by which two different trackers link the IDs they’ve given to the same user. The most common use of cookie syncing is to enable real-time bidding between several entities in an ad auction. It allows the bidder and the ad network to refer to the user by the same ID so that the bidder can place bids on a particular user in current and future auctions. Cookie syncing raises subtle yet serious privacy concerns, but due to the technical complexity of explaining it, didn’t receive much press coverage. In this post I’ll explain cookie syncing and why it’s worrisome — even more so than canvas fingerprinting.
[This is the first in a series of posts giving some examples of security-related research in the Princeton computer science department. We’re actively recruiting top-notch students to enter our Ph.D. program, as well as postdocs and visiting scholars. We don’t have enough bandwidth here on the blog to feature everything we do, so we’ll be highlighting a few examples over the next couple of weeks.]
Everything we do on the web is tracked, profiled, and analyzed. But what do companies do with that information? To what extent do they use it in ways that benefit us, versus discriminatory ways? While many concerns have been raised, not much is known quantitatively. That’s why at Princeton we’re building an infrastructure to detect, measure and reverse engineer differential treatment of web users.