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SIH 2026

Smart India Hackathon · sih.gov.in

226 statements
SoftwareBlockchain & CybersecuritySIH26182

Automated Attribution of Unknown Cryptocurrency Wallets to Nearest Virtual Asset Service Providers (VASPs) through Blockchain Intelligence APIs

Ministry of Home Affairs

Open sih.gov.in
Organisation
Ministry of Home Affairs
Department
Indian Cyber Crime Coordination Centre (I4C),CIS Division
Category
Software
Theme
Blockchain & Cybersecurity
Submission deadline
20 September 20262026-09-20
Ideas submitted
0/500
Serial number
182
Data captured on
2026-08-23
Dataset link
No dataset link published
Contact info
No contact published
Youtube link
No video published
Problem brief

• Background The rapid adoption of Virtual Digital Assets (VDAs) and decentralized blockchain ecosystems has significantly increased the complexity of cybercrime investigations globally. Law Enforcement Agencies (LEAs) frequently encounter cryptocurrency wallet addresses linked to cyber frauds, ransomware, investment scams, darknet activities, and laundering of crime proceeds. Under the existing investigation workflow, LEAs raise lawful information disclosure requests through the SAHYOG Portal to Virtual Asset Service Providers (VASPs) such as crypto exchanges, custodial wallet providers, and trading platforms. However, in many cases, the suspect wallet identified during investigations belongs to an unhosted wallet or a wallet for which the associated VASP is unknown. This creates major delays in attribution, freezing of assets, and identification of the beneficial owner. Blockchain transactions generally pass through multiple intermediary wallets before reaching centralized exchanges. Identifying the 'nearest direct deposit accepting exchange' manually through blockchain analysis is time-consuming and requires specialized expertise.

• Description The proposed system envisages development of an Automated Blockchain Intelligence & VASP Attribution Engine integrated with the SAHYOG Portal through APIs. The system should:

  • Automatically analyze suspect cryptocurrency wallet addresses reported during investigations on the Sahyog Platform
  • Automatically trace blockchain transaction paths to identify:

o nearest centralized exchange, o custodial wallet service, o or VASP receiving direct deposits from the suspect wallet.

• Map blockchain of deposit addresses and transaction flows across multiple blockchain networks such as: o Bitcoin, o Ethereum, o Tron, o BNB Chain, o Solana, o Polygon o and other major chains.

• Support identification of: o exchange clusters, o hot wallets, o deposit wallets, o mixers/tumblers, o DeFi bridges, o and cross-chain swap services.

  • Integrate Sahyog with blockchain intelligence APIs and graph analytics engines.
  • Provide automated tagging and confidence scoring for suspected VASPs.
  • Generate investigation-ready reports for LEAs.
  • Assist investigators in automatically routing lawful disclosure or freezing requests to the correct VASP through the SAHYOG Portal.

The system may additionally support:

  • visualization of fund movement,
  • cross-chain transaction mapping,
  • risk scoring,
  • identification of laundering typologies,
  • and alerting for high-risk wallets linked to ransomware, darknet, terrorism financing, or fraud ecosystems.
  • Expected Solution A software-based blockchain intelligence platform integrated with the SAHYOG ecosystem capable of:
  • Automated identification of nearest VASP/exchange linked to unknown wallets.
  • API-driven blockchain tracing and attribution support.
  • Multi-chain transaction analysis and visualization.
  • Real-time generation of investigative intelligence.
  • Risk classification of wallets and transaction flows.
  • Dashboard for LEAs with case-based analytics and reporting.
  • Scalable architecture capable of handling large-volume blockchain transaction analysis.

The solution should aim to:

  • reduce investigation time,
  • improve asset freezing efficiency,
  • enhance attribution capabilities,
  • and strengthen cross-border cybercrime investigations involving VDAs
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