Anonymous Card Shuffling and its Applications to Parallel Mixnets

We study the question of how to shuffle n cards when faced with an opponent who knows the initial position of all the cards and can track every card when permuted, except when one takes K < n cards at a time and shuffles them in a private buffer “behind your back, ” which we call buffer shuffling. The prob-lem arises naturally in the context of parallel mixnet servers as well as other security applications. Our analysis is based on related analyses of load-balancing processes. We include extensions to variations that involve corrupted servers and adversarially injected messages, which correspond to an opponent who can peek at some shuffles in the buffer and who can mark some number of the cards. In addition, our analysis makes novel use of a sum-of-squares metric for anonymity, which leads to improved per-formance bounds for parallel mixnets and can also be used to bound well-known existing anonymity measures.