2012 Poster Sessions : Neuroscience Meets Cryptography: Implicit Credential Learning

Student Name : Hristo Bojinov
Advisor : Dan Boneh
Research Areas: Computer Systems
Abstract:
Coercing users to disclose their credentials (a.k.a. rubber-hose attacks) has been the bane of classic cryptography. We present our ongoing work on designing coercion-resistant security primitives based on implicit learning. We show our current results as well as experimental setup using Amazon's Mechanical Turk service. We also map out directions for future work that we plan to pursue.

Bio:
Hristo Bojinov is a Ph.D. candidate at Stanford's Security Lab. His work on mobile and web security is advised by Prof. Dan Boneh. Prior to Stanford, Hristo spent a number of years in industry, building enterprise software and storage security products. Hristo has a M.S. from Stanford University, and S.B. from MIT.