Real-Time Identification of Fraud-Linked Cryptocurrency Exchanges from Victim-Reported Suspect Wallet Addresses through Automated Blockchain Analytics

Official description

• Background Cyber fraud victims increasingly report suspect cryptocurrency wallet addresses used by fraudsters for collection of funds in cases involving: • investment scams, • task-based frauds, • sextortion, • ransomware, • phishing, • darknet transactions, • and organized cyber-enabled financial crimes. During investigations, the reported wallet addresses are often: • non-custodial wallets, • temporary burner wallets, • or intermediary wallets used for layering and laundering. The inability to quickly identify the cryptocurrency exchange or VASP associated with these wallets delays: • freezing of assets, • preservation of evidence, • tracing of fund flows, • and victim fund recovery. Manual blockchain tracing requires significant technical expertise and time, particularly in cases involving: • multi-chain transfers, • DeFi protocols, • mixers/tumblers, • bridges, • and privacy-enhancing mechanisms. • Description The proposed solution envisages a Real-Time Crypto Fraud Attribution System capable of automatically analyzing victim-reported wallet addresses and identifying the nearest exchange or VASP receiving direct deposits. The system should: • ingest wallet addresses reported through cybercrime complaint systems, • automatically perform blockchain tracing, • identify associated exchanges or VASPs, • detect fund movement patterns, • and generate actionable intelligence for investigators. Key features may include: • blockchain transaction graph analysis, • clustering of exchange wallets, • detection of intermediary laundering wallets, • identification of cross-chain fund movement, • integration with SAHYOG and NCRP platforms, • automated alert generation, • and risk categorization of wallets. The system should support multiple blockchain ecosystems and provide: • real-time tracing capability, • automated investigative recommendations, • and analytics dashboards for law enforcement agencies • Expected Solution A software platform capable of: • real-time blockchain intelligence generation, • automated VASP identification, • tracing of suspect wallets, • cross-chain transaction analytics, • fund-flow visualization, • integration with LEA systems, • and generation of standardized investigation reports. The system should: • reduce response time in cyber fraud investigations, • improve freezing of proceeds of crime, • enhance coordination with VASPs, • and strengthen digital evidence collection capabilities. The platform should further support: • API integrations, • scalable blockchain indexing, • AI/ML-assisted risk detection, • and automated pattern recognition for fraud typologies.