Benford’s Wallet

Abstract

As blockchain transactions are public, it may be possible to infer a user's identity or activity by studying the statistical features of their transactions. For instance, Benford's Law analysis can identify anomalies in the probability distribution of the leading digits of the entries in a numerical dataset. The anomalies can then be used for further analysis that leads to the exposure of privacy or business secrecy. In this paper, we propose a wallet design which randomly splits a payment value over multiple transactions in such a way that it is resistant to Benford's Law analysis, and therefore preventing any further analysis on the transaction data. We support our claim by providing a mathematical proof showing that the resulting distribution of the leading digits of the transaction values adhere closely to the Benford's Law, thus improving user privacy. Moreover, our design preserves accountability for any misbehaviour by creating an off-chain cryptographic link between a payment and its respective transactions which can be provided upon request during a legitimate audit.