Etherscan, the leading blockchain explorer for the Ethereum blockchain that allows users to search and validate transactions occurring on the network, will be introducing an analytical tracing solution based on a machine learning system, the Taint Inference Analysis Engine to pinpoint funds or addresses suspected of engaging in illicit activity.
For years, Etherscan has been working manually on identifying compromised and tainted addresses and the process is often time-consuming. To address this problem, ETHProtect can now track the origins of funds and determine if they are compromised, such as in the cases of scams, phishing or hacks.
Etherscan will flag suspicious addresses based on user reports and add them to a database, while users on the frontend interface can identify these flagged addresses with a ‘Red Shield Icon’, indicating that these particular addresses have come into contact with compromised funds.
“Once the tainted address is identified, any transfer of tainted funds from its origin is traced and highlighted up to the latest block. The tracing is never static; the engine constantly traces and identifies any newly tainted addresses. This helps users track the flow of tainted funds in real time,” the post reads.
While this is not a novel solution, Etherscan points out that tracing solutions can often be very costly when offered as a service by third-party providers. By enabling ETHProtect, Etherscan can make information on fraudulent transactions more readily available to all its users.
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