Echoes of the Past: Recovering Blockchain Metrics from Merged Mining

So far, the topic of merged mining has mainly been considered in a security context, covering issues such as mining power centralization or cross-chain attack scenarios. In this work we show that key information for determining blockchain metrics such as the fork rate can be recovered through data e...

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Bibliographic Details
Published inFinancial Cryptography and Data Security Vol. 11598; pp. 527 - 549
Main Authors Stifter, Nicholas, Schindler, Philipp, Judmayer, Aljosha, Zamyatin, Alexei, Kern, Andreas, Weippl, Edgar
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2019
Springer International Publishing
SeriesLecture Notes in Computer Science
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Summary:So far, the topic of merged mining has mainly been considered in a security context, covering issues such as mining power centralization or cross-chain attack scenarios. In this work we show that key information for determining blockchain metrics such as the fork rate can be recovered through data extracted from merge mined cryptocurrencies. Specifically, we reconstruct a long-ranging view of forks and stale blocks in Bitcoin from its merge mined child chains, and compare our results to previous findings that were derived from live measurements. Thereby, we show that live monitoring alone is not sufficient to capture a large majority of these events, as we are able to identify a non-negligible portion of stale blocks that were previously unaccounted for. Their authenticity is ensured by cryptographic evidence regarding both, their position in the respective blockchain, as well as the Proof-of-Work difficulty. Furthermore, by applying this new technique to Litecoin and its child cryptocurrencies, we are able to provide the first extensive view and lower bound on the stale block and fork rate in the Litecoin network. Finally, we outline that a recovery of other important metrics and blockchain characteristics through merged mining may also be possible.
ISBN:9783030321000
3030321002
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-32101-7_31