Binance, don't rush to brag, let's identify the bugs in this Alpha airdrop first.
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Targeting Airdrop 'Wool Gatherers': How to Use AI Technology to Identify 90% of Witch Addresses?
The Binance risk control team, in collaboration with academia, has proposed a new detection system based on 'AI + blockchain graph analysis' to detect witch addresses. How does it achieve this?
Written by: Nicky, Foresight News
Recently, the Binance risk control department, in collaboration with Zand AI and ZEROBASE, published a paper on witch attacks. To help readers quickly understand the core content of the paper, the author summarized the following core points after studying the paper.
In cryptocurrency airdrop activities, there is always a group of special players operating in the shadows. They are not ordinary users but use automated scripts to create hundreds or even thousands of fake addresses in bulk — these are the notorious 'witch addresses.' These addresses attach themselves like parasites to the airdrop activities of well-known projects like Starknet and LayerZero. They eat away at the project budget, dilute real user rewards, and undermine the foundation of blockchain fairness.
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