Significant Digits: Using Large-Scale Blockchain Data to Predict Fraudulent Addresses. (arXiv:2301.01809v1 [cs.CR])

Blockchain systems and cryptocurrencies have exploded in popularity over the
past decade, and with this growing user base, the number of cryptocurrency
scams has also surged. Given the graphical structure of blockchain networks and
the abundance of data generated on these networks, we use graph mining
techniques to extract essential information on transactions and apply Benford's
Law to extract distributional information on address transactions. We then
apply a gradient-boosting tree model to predict fraudulent addresses. Our
results show that our …

address addresses base blockchain cryptocurrencies cryptocurrency data extract fraudulent generated information large law mining networks predict scale scams systems techniques transactions