Privacy-preserving payments in credit networks

Apr 13, 2016

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Abstract

A credit network models trust between agents in a distributed environment and enables payments between arbitrary pairs of agents. With their flexible design and robustness against intrusion, credit networks form the basis of several Sybil-tolerant social networks, spam-resistant communication protocols, and payment systems.

In the first half of the talk, we introduce the concept of credit network and its application in the currently deployed Ripple payment system. We further characterize the privacy issues in Ripple as the result of clustering heuristics to group wallets based on observations on the publicly available Ripple network graph. In the second half of the talk, we show PrivPay, the first provably secure privacy-preserving payment protocol for credit networks. The distinguishing feature of PrivPay is the computation of the maximal credit between two agents without revealing any information about the credit network, the transaction or the agents themselves. Finally, we present our results on privacy-preserving payments on a distributed credit network, where each agent locally stores its own financial information.