Year: 2012
Type: preprint
Abstract: We study the question of how to shuffle $n$ cards when faced with an opponent who knows the initial position of all the cards {\em and} can track every card when permuted, {\em except} when one takes $K< n$ cards at a time and shuffles them in a private buffer "behind your back," which we call {\em buffer shuffling}. The problem 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 performance bounds for parallel mixnets and can also be used to bound well-known existing anonymity measures.
Source: arXiv (Cornell University)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: HCC: Medium: Collaborative Research: Data-Parallel Hash Tables: Theory, Practice and Applications, G2998923865, IPS: Collaborative Research: Privacy Management, Measurement, and Visualization in Distributed Environments, G4154686922, SDCI Data New: Trust Management for Open Collaborative Information Repositories: The CalSWIM Cyberinfrastructure, EAGER: Usable Location Privacy in Geo-Social Networks, TC: Large: Collaborative Research: Towards Trustworthy Interactions in the Cloud, NeTS FIND: A Network-Wide Hashing Infrastructure for Monitoring and Measurement, AF : Small : The Theory and Practice of Hash-Based Algorithms and Data Structures, TC:Large:Collaborative Research: Towards Trustworthy Interactions in the Cloud, G8876996369
OpenAlex ID: W2949413723