Bit Jungle has independently developed the AI big data platform - Zhong Kui System, which combines AI and big data technology to support efficient on-chain traceability, cross-chain analysis, and address monitoring, covering over 200 million entity labels, and can quickly identify and track suspicious activities.
The functions of Bit Jungle's Zhong Kui System include:
1) Visualizing on-chain fund relationships for precise traceability. By using on-chain address graphs, the transaction relationships between multiple addresses are visualized, clearly displaying the flow of suspicious funds; combined with the label system (hacker addresses, scam addresses, money laundering addresses, etc.), it helps users quickly identify high-risk addresses.
2) Real-time monitoring of suspicious transactions with precise alerts. Real-time monitoring of specified addresses is supported, targeting high-risk targets such as hacker wallets, risky exchanges, and scam addresses; custom monitoring conditions include large transaction transfers, Tornado mixing, cross-chain transfers, MeMe coin money laundering, etc. Once suspicious transactions are detected, alerts are triggered immediately to notify users, helping organizations respond to risks promptly.
3) AML risk assessment. By analyzing transaction behaviors through AI algorithms, risk scores are provided for each transaction to identify potential illegal fund flows; scoring rules cover multiple dimensions including address blacklists, large transaction frequencies, cross-chain jump counts, and whether entering mixers, supporting API integration that can be embedded into exchanges and risk control systems, providing real-time risk control solutions.
Today, with advanced technological means and rich experience, Bit Jungle has become the most trusted provider of virtual currency traceability and asset recovery services in the industry, helping clients recover stolen virtual assets in the fastest and safest way possible.
