Correlations of Multi-input Monero Transactions
This work addresses privacy vulnerabilities in Monero for cryptocurrency users, but it is incremental as it adds a heuristic to existing denoising methods.
The paper tackled the problem of identifying real inputs in Monero's RingCT transactions by detecting statistical correlations in transaction timestamps, which improved the accuracy of denoising the blockchain with calculated probability adjustments.
A variety of correlations are detected in the Monero blockchain. The joint distribution of the time-since-last-transaction between elements of pairs of RingCTs is enhanced in comparison with the product of the marginal distributions. Similarly there is an enhancement in the joint distribution of the hour timestamps between the same pairs. Lastly, we find another enhancement when the correlation is measured between the hour timestamps of the transaction itself and the elements of the RingCTs. We calculate some adjustments to the probabilities of which input in a RingCT is real, providing an additional heuristic to denoising the Monero blockchain.