24/02/2019
JoinMarket has a tumbler application which aims to send bitcoins in a way that delinks the origin and destination.
I have some thoughts on how and why to improve the tumbler algorithm.
Feel free to bikeshed some of these parameters (averages, counts, etc), as my important points are about other stuff.
| #!/usr/bin/env python | |
| from __future__ import print_function | |
| """ | |
| Find/count JM transactions in blocks. | |
| Ensure your joinmarket-clientserver virtualenv (jmvenv) is activated, | |
| make sure your Bitcoin Core node is available and joinmarket.cfg is appropriately set. | |
| Pass start and end block number: | |
| `python jmtxfinder.py 400000 400200`. |
| 1/ About the nature of Payjoin Transactions and Deception Tools | |
| I'm used to describe Payjoin Transactions as Steganographic Transactions but they can also be described more generally as "Deception Tools" (https://medium.com/@laurentmt/hi-ilya-e72ddda60b35). | |
| In my humble opinion, the use of deception tools is a legit and effective strategy for improving on-chain privacy but it's important to keep in mind that the deception game has its own rules and these rules are very different from others approaches (like "privacy backed by maths" tools). | |
| An important principle of this deception game is that it must introduces and preserves some kind of morphism between interpretations. It should be absolutely impossible for an analyst to distinguish between one form and the other. | |
| For instance, we have: |
There are a bunch of possible reasons for a force close - I will elaborate on the most common ones.
⚠ This is a work in progress and will get expanded.
WHAT HAPPENED?
An HTLC (a lightning transaction) timed out, which means it did neither succeed in arriving at it's