US 11,907,942 B2
Blockchain network risk management universal blockchain data model
Antoine J. M. Le Calvez, Treverec (FR); Lucas A. Nuzzi, New York, NY (US); Samuel Wyner, Albertson, NY (US); Kevin Julian Bornatsch, Jersey City, NJ (US); and Salvatore Joseph Ternullo, Medford, MA (US)
Assigned to COIN METRICS INC., Boston, MA (US)
Filed by COIN METRICS INC., Cambridge, NJ (US)
Filed on Apr. 30, 2021, as Appl. No. 17/245,161.
Claims priority of provisional application 63/065,347, filed on Aug. 13, 2020.
Claims priority of provisional application 63/019,135, filed on May 1, 2020.
Prior Publication US 2021/0342825 A1, Nov. 4, 2021
Int. Cl. G06Q 20/38 (2012.01); G06F 21/55 (2013.01); G06F 16/23 (2019.01); G06Q 20/40 (2012.01)
CPC G06Q 20/389 (2013.01) [G06F 16/2379 (2019.01); G06F 21/554 (2013.01); G06Q 20/4016 (2013.01); G06F 2221/034 (2013.01); G06Q 2220/00 (2013.01)] 22 Claims
OG exemplary drawing
 
12. A method for implementing blockchain network risk management, the method comprising the steps of:
receiving, via a data interface, transaction data from a plurality of data sources, wherein the data interface communicates with the plurality of data sources through a communication network via an application programming interface, the plurality of data sources comprising relay protocols, client nodes, mining pool protocols and hashrate rental marketplaces, the data interface further comprising a data feed interface;
accessing, via a mempool querying engine, data relating to unprocessed transactions stored in a memory pool;
accessing, via a mining pool verifier, block hash data from a plurality of mining pools;
accessing, via a hashrate price collector, rates data from one or more hashrate rental marketplaces relating to mining supply and demand information;
based at least in part on the block hash data from the plurality of mining pools and the rates data from the one or more hashrate rental marketplaces, generating, by a network processor, a network attack risk that represents a risk of network disruption;
based at least in part on the transaction data, generating, by a settlement processor, a settlement risk that includes one or more dynamic thresholds that reflect one or more events being experienced by a network that could prevent settlement;
based at least in part on data relating to the unprocessed transactions stored in the memory pool, generating, by a fee processor, a fee volatility risk that identifies an abnormal change in one or more of: mempool transaction fees and mempool transaction count;
based at least in part on the transaction data, generating, by an event processor, a network event alert that represents unexpected inflation in real-time; and
generating, via an interactive user interface, at least one alert that represents an indication of risk comprising a combination of the network attack risk, the settlement risk, the fee volatility risk and an unusual network event risk.