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    Home»Markets»Bybit and HKU College students Collaborate on Anti-Cash Laundering Analysis Via Actual-World Demixing Problem | UseTheBitcoin
    Bybit and HKU College students Collaborate on Anti-Cash Laundering Analysis Via Actual-World Demixing Problem | UseTheBitcoin
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    Bybit and HKU College students Collaborate on Anti-Cash Laundering Analysis Via Actual-World Demixing Problem | UseTheBitcoin

    By Crypto EditorMay 15, 2026No Comments5 Mins Read
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    DUBAI, UAE, Could 15, 2026 /PRNewswire/ — Bybit, the world’s second-largest cryptocurrency trade by buying and selling quantity, not too long ago concluded an anti-money laundering analysis collaboration with scholar groups from The College of Hong Kong (HKU), giving members sensible expertise in cryptocurrency investigations, machine studying and anti-money laundering evaluation by means of a real-world demixing problem.

    The collaboration centered on the February 2025 Bybit safety breach. Utilizing the incident as a case examine, college students explored how blockchain analytics and machine studying could be utilized to establish laundering pathways related to cryptocurrency mixer exercise and transactions linked to the Lazarus Group.

    The mission was proposed and supervised by Prof. Doyeon Kim, assistant professor in Accounting and Regulation at The College of Hong Kong, with Bybit offering the real-world investigative context and trade steerage all through the analysis course of. This capstone was scoped and sponsored by David Zong, Head of group threat management and safety at Bybit, to present college students the chance to deal with a real-world trade problem fairly than a hypothetical train. Zong has intently adopted the crew’s findings and progress all through the mission.

    As a part of the collaboration, college students have been tasked with tracing Lazarus-linked funds on the Bitcoin blockchain, understanding the function of pockets addresses used throughout laundering operations, and creating machine studying approaches able to figuring out mixer-related transaction patterns and potential output addresses related to illicit exercise. Given the privacy-preserving design of cryptocurrency mixers, tracing precise transaction flows is mathematically infeasible, which means there is no such thing as a absolute or deterministic technique for attribution. The mission subsequently targeted on probabilistic evaluation, behavioral clustering and machine studying strategies designed to enhance the identification of suspicious transaction patterns and laundering pathways.

    Moderately than following a hard and fast methodology, college students got an open mission temporary and inspired to outline their very own analytical method. Some groups expanded on current blockchain tracing strategies, whereas others explored various machine studying and graph-analysis fashions.

    Over a number of weeks of analysis and iteration, scholar groups refined their methodologies by means of impartial investigation, technical discussions and mission evaluations. Bybit additionally performed a mid-term evaluation session with collaborating groups, creating a possibility for college students to current progress updates, mirror on analysis findings and obtain suggestions to help the following stage of improvement.

    The collaboration was designed to show college students to the uncertainty and problem-solving calls for generally related to real-world anti-money laundering and blockchain compliance work. For college kids, the expertise supplied a possibility to refine analytical considering, develop technical frameworks and work by means of advanced investigative challenges with out predetermined options. For Bybit, the initiative supported engagement with rising expertise whereas permitting the corporate to contribute sensible trade views to educational analysis and early-stage technical exploration.

    The ultimate mission evaluation was held on the Bybit workplace, the place college students offered their findings and acquired further suggestions from the Bybit crew.

    As a part of the analysis course of, college students analyzed roughly 49,800 Bitcoin blocks and greater than 146 million transactions utilizing clustering fashions, graph neural networks and graph-based transaction evaluation strategies.

    In line with the mission findings, the analysis recognized 10,289 Wasabi-like transactions and generated a blockchain transaction subgraph containing greater than 1.6 million tackle nodes and almost 6 million transaction edges utilizing Peel Chain methodology. Primarily based on their sampling and testing, a machine studying cluster achieved a 70.5% recall charge towards confirmed DPRK linked addresses.

    The mission moreover examined how cryptocurrency mixers corresponding to Wasabi, CoinJoin transactions and peel chain buildings are used to obscure transaction histories and complicate anti-money laundering investigations. College students studied how illicit funds transfer throughout wallets, decentralized exchanges, swap protocols and cross-chain methods designed to scale back transaction traceability.

    College students concerned within the collaboration stated the mission helped them higher perceive how blockchain investigations, anti-money laundering methods and cryptocurrency safety operations operate in observe.

    One participant stated the expertise bolstered the significance of regulation and anti-money laundering applied sciences in growing operational obstacles for prison actors whereas additionally demonstrating the complexity of fixing sensible trade issues.

    One other scholar described the mission as extra informative and interesting than anticipated and stated the training outcomes exceeded preliminary expectations.

    A number of members stated the collaboration supplied beneficial perception into cryptocurrency investigations, blockchain safety incidents and the growing demand for expertise in blockchain safety and compliance-related fields.

    One scholar additionally famous that the mission contributed to a extra systematic understanding of Bitcoin blockchain buildings, transaction mechanisms and the logic behind on-chain cash laundering, whereas discussions surrounding the way forward for blockchain-based monetary methods supplied helpful views associated to future profession improvement in finance and actuarial science.

    The collaboration displays rising curiosity amongst universities and digital asset corporations in making use of machine studying and blockchain analytics to real-world cybersecurity, compliance and monetary crime challenges.

    Bybit extends its appreciation to the HKU Enterprise Faculty and Professor Kim for his or her collaboration and help all through the analysis initiative.

    #Bybit  / #NewFinancialPlatform

    Bybit and HKU College students Collaborate on Anti-Cash Laundering Analysis Via Actual-World Demixing Problem | UseTheBitcoin

    About Bybit

    Bybit is the world’s second-largest cryptocurrency trade by buying and selling quantity, serving a world neighborhood of over 80 million customers. Based in 2018, Bybit is redefining openness within the decentralized world by creating a less complicated, open and equal ecosystem for everybody. With a powerful concentrate on Web3, Bybit companions strategically with main blockchain protocols to supply sturdy infrastructure and drive on-chain innovation. Famend for its safe custody, various marketplaces, intuitive consumer expertise, and superior blockchain instruments, Bybit bridges the hole between TradFi and DeFi, empowering builders, creators, and fans to unlock the total potential of Web3. Uncover the way forward for decentralized finance at Bybit.com.

    For extra particulars about Bybit, please go to Bybit Press

    For media inquiries, please contact: [email protected]

    For updates, please comply with: Bybit’s Communities and Social Media

    Discord | Fb | Instagram | LinkedIn | Reddit | Telegram | TikTok | X | Youtube

    (PRNewsfoto/Bybit)





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