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Echoes of the Past: Recovering Blockchain Metrics from Merged Mining

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Authors
Nicholas Stifter
Philipp Schindler
Aljosha Judmayer
Alexei Zamyatin
Andreas Kern
Edgar Weippl
Published in
Financial Cryptography and Data Security
Publisher
Springer International Publishing

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Abstract

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.

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previous chapter Sprites and State Channels: Payment Networks that Go Faster Than Lightning
next chapter TxProbe: Discovering Bitcoin’s Network Topology Using Orphan Transactions
Title
Echoes of the Past: Recovering Blockchain Metrics from Merged Mining
Authors
Nicholas Stifter
Philipp Schindler
Aljosha Judmayer
Alexei Zamyatin
Andreas Kern
Edgar Weippl
Copyright Year
2019
Book
Financial Cryptography and Data Security

Print ISBN: 978-3-030-32100-0

Electronic ISBN: 978-3-030-32101-7

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-32101-7_31
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