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The original was posted on /r/monero by /u/OverEducation6572 on 2024-10-26 16:38:08+00:00.

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I randomly sampled 100,000 Monero transactions between blocks 2.75 million and 3.25 million and recorded the age of each decoy. I then fitted a lognormal distribution to this data and used its parameters to generate new wait times. While the distributions are not perfectly aligned, they are very close.

The way it works is as follows: after receiving Monero, you would use the Monero Churn Timer to generate a random wait time. You would then set a reminder to “churn” (i.e., send that transaction to yourself at a new address) after the specified time. If necessary, you could repeat this process.

Disclaimer: Churning could potentially make your transactions more identifiable, rather than more private, especially if you are not sampling from the full empirical distribution across all relevant factors. These factors include, but are not limited to, the number of inputs and outputs, the time of day, and other aspects such as whether you are using a remote node. Mismanaging these variables may increase the risk of transaction fingerprinting.