Team: Ravi Bhandia (IEOR), Charles Garnot (CEE), Yijun Liang (IEOR), Fuhua Liu (IEOR), Francesco Piccoli (IEOR), Salome Schwarz (CEE), Yuyang Zhao (IEOR)
Advisors: Doug Purdy (xPring / Ripple), Paul Grigas (IEOR)
Since 2017, the beginning of speculation over cryptocurrencies, price volatility has become a barrier for daily use of cryptocurrencies, including Ripple’s XRP. In order to enhance adoption of XRP as a medium of exchange, a technical requirement is to catch and prevent behaviors that may cause unstable prices. Our team is creating a detection system to identify abnormal activities using machine learning models. We analyze unexpected events in transaction volume, fee increases, and account creation. A Slackbot will report our analysis and send timely alerts to Ripple’s engineers so they can take measures that will improve confidence in XRP value.
The XRP Ledger
Visualized below, where each node represents an account and each connections is a transaction between accounts. On the XRP Ledger, assets like Bitcoin or USD can be exchanged through the medium of XRP, Ripple’s cryptocurrency.
Creating the new Internet of value, where money moves like information moves today: instantly, reliably, and for fractions of a penny.
Our bot provides real-time notifications on anomalies of the ledger, allowing Ripple’s community to be promptly informed of possible network attacks to be able to intervene fast. Anomalies are detected based on previous analysis of historical data, like the number of daily accounts created.
Digging into the large amount of information produced by the XRP ledger can be overwhelming. To facilitate this informational process, we instituted a weekly report to be sent out on Mondays, summarizing what happened on the ledger the week before.
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