DNS Cache-Based User Tracking

Amit Klein (Bar Ilan University), Benny Pinkas (Bar Ilan University)

We describe a novel user tracking technique that is based on assigning statistically unique DNS records per user. This new tracking technique is unique in being able to distinguish between machines that have identical hardware and software, and track users even if they use “privacy mode” browsing, or use multiple browsers (on the same machine).
The technique overcomes issues related to the caching of DNS answers in resolvers, and utilizes per-device caching of DNS answers at the client. We experimentally demonstrate that it covers the technologies used by a very large fraction of Internet users (in terms of browsers, operating systems, and DNS resolution platforms).
Our technique can track users for up to a day (typically), and therefore works best when combined with other, narrower yet longer-lived techniques such as regular cookies - we briefly
explain how to combine such techniques.
We suggest mitigations to this tracking technique but note that it is not easily mitigated. There are possible workarounds, yet these are not without setup overhead, performance overhead or convenience overhead. A complete mitigation requires software modifications in both browsers and resolver software.