CyLab Usable Privacy and Security Lab / Privacy Seminar

  • Ph.D. Student
  • Ph.D. Program in Societal Computing
  • IInstitute for Software Research, Carnegie Mellon University

Can Unicorns Help Users Compare Crypto Key Fingerprints?

Many authentication schemes ask users to manually compare compact representations of cryptographic keys, known as fingerprints. If the fingerprints do not match, that may signal a man-in-the-middle attack. An adversary performing an attack may use a fingerprint that is similar to the target fingerprint, but not an exact match, to try to fool inattentive users. Fingerprint representations should thus be both usable and secure.

We tested the usability and security of eight fingerprint representations under different configurations. In a 661-participant between-subjects experiment, participants compared fingerprints under realistic conditions and were subjected to a simulated attack. The best configuration allowed attacks to succeed 6% of the time; the worst 72%. We find the seemingly effective compare-and-select approach performs poorly for key fingerprints and that graphical fingerprint representations, while intuitive and fast, vary in performance. We identify some fingerprint representations as particularly promising.

Practice talk for CHI

Josh Tan is a 3rd year PhD student in the Societal Computing program advised by Lorrie Cranor and Lujo Bauer.

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