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.

View More Papers

YODA: Enabling computationally intensive contracts on blockchains with Byzantine...

Sourav Das (Department of Computer Science and Engineering, Indian Institute of Technology Delhi), Vinay Joseph Ribeiro (Department of Computer Science and Engineering, Indian Institute of Technology Delhi), Abhijeet Anand (Department of Computer Science and Engineering, Indian Institute of Technology Delhi)

Read More

DIAT: Data Integrity Attestation for Resilient Collaboration of Autonomous...

Tigist Abera (Technische Universität Darmstadt), Raad Bahmani (Technische Universität Darmstadt), Ferdinand Brasser (Technische Universität Darmstadt), Ahmad Ibrahim (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Matthias Schunter (Intel Labs)

Read More

Time Does Not Heal All Wounds: A Longitudinal Analysis...

Meng Luo (Stony Brook University), Pierre Laperdrix (Stony Brook University), Nima Honarmand (Stony Brook University), Nick Nikiforakis (Stony Brook University)

Read More

TextBugger: Generating Adversarial Text Against Real-world Applications

Jinfeng Li (Zhejiang University), Shouling Ji (Zhejiang University), Tianyu Du (Zhejiang University), Bo Li (University of California, Berkeley), Ting Wang (Lehigh University)

Read More