Bitcoin Burn Addresses: Unveiling the Permanent Losses and Their Underlying Causes
ID: cool-data-embedded-in-the-bitcoin-blockchain/bitcoin-burn-addresses-unveiling-the-permanent-losses-and-their-underlying-causes
Bitcoin Burn Addresses: Unveiling the Permanent Losses and Their Underlying Causes by 
Ciro Santilli 35 Updated 2025-03-25 +Created 2025-03-24
Ciro Santilli 35 Updated 2025-03-25 +Created 2025-03-24By Mohamed el Khatib and Arnaud Legout.
Both autors were at Inria Centre at Université Côte d'Azur, Mohamed the intern and Arnaud the Inria researcher employee.
Cool, this method could reveal novel P2FKH images:208,656 addresses suspected to be burn addresses because they have a low Shannon entropyUnfortunately their method might not be well suited for finding images, later on:
We propose a methodology to automatically detect burn addresses. We manually classified
Our model identified 7,905 true burn addresses from a pool of 1,283,997,050 addresses with only 1,767 false positive.
Storing images for fun and posterity. We did not observe plain text messages encoded in Bech32 addresses. As our methodology is designed to identify burn addresses with a human-readable structure or easily identifiable patterns, we are not supposed to detect images encoded in burn addresses.
Data for their results can be found at:
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