Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
The fair exchange problem is key to trading electronic items in systems of mutually untrusted parties. In modern variants of such systems, each party is equipped with a security module. The security modules trust each other but can only communicate by exchanging messages through their untrusted host parties,that could drop those messages. We describe a synchronous algorithm that ensures deterministic fair exchange if a majority of parties are honest, which is optimal in terms of resilience. If there is no honest majority, our algorithm degrades gracefully: it ensures that the probability of unfairness can be made arbitrarily low. Our algorithm uses, as an underlying building block, an early-stopping subprotocol that solves, in a general omission failure model, a specific variant of consensus we call biased consensus. Interestingly, this modular approach combines concepts from both cryptography and distributed computing, to derive new results on the classical fair exchange problem.