We build analyses and tools to study blockchain systems from an empirical data science perspective.
Decentralized consensus systems produce large amounts of canon data - block headers, miner-reported timestamps, nonces, transaction data - complemented by even larger amounts of ephemeral metadata - propagation pathways, receipt timestamps, alternative histories. We seek the signal in the noise: the anomalies, the edge cases, the subtle temporal and heuristic signatures. We curate a unique dataset that enables endless new types of analyses. Our work is shared freely. Analyses and research have covered Monero, Loki, Zcash, and other privacy coins.
The Noncesense Archival Network (formerly known as the Monero Archival Project) runs blockchain daemons with custom software extensions that provide standard public blockchain service with the extra capability to capture orphaned blocks, node-centric metadata, and other usually discarded phenomena. Our nodes are deployed globally to capture a broader view of the network and enable representative analyses.
We are currently observing the Monero and Loki blockchains. Contact us if you are interested in expansion.
Analyses of alternative chains and reorganization events, combined with node receipt timestamp metadata, enables detection of various mining phenomena. For example, we observed probable selfish/stubborn mining on the Monero blockchain, and curious Merlin blocks with timestamps preceding their parent.
For a supposedly useless number, nonces contain a surprising degree of narrative. Noncesense Research Lab revealed signatures of multiple unique nonce search strategies being used in current mining operations for Monero, Loki, and Aeon. On multiple occasions, nonce trends have been connected with specialized mining equipment (ASICs).
We discovered weaknesses in CryptoNote's dynamic block size algorithm (Big Bang Attack) and are exploring fresh approaches for a long-term solution. We also provide data to inform consensus rules to eliminate non-fungible transactions.
The peer-to-peer networks enabling decentralized consensus systems are complex organisms whose topology, connectivity, and latency significantly impact message propagation times and routes. The study of node variability and volatility characteristics over multiple timescales can inform connection best practices, such as active defensive measures.
Noncesense Research Lab is a not-for-profit ad hoc collective of volunteers producing free and open-source software (FOSS) tools and analyses for general public use. Our infrastructure costs are currently supported out-of-pocket by individual contributors who would greatly appreciate additional support in bearing these expenses.
Donations to help keep the lights on can be sent to:
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wpjbHsBSUviz44prcgiPXpHxeaFjHYCq824VjLtM19HjWGv
View key:
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Thanks to JetBrains for the free open source license package to enable our research and development.
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