Privacy-Preserving De-Duplication Platform for Welfare Beneficiary Databases

Objective: Develop a secure digital solution to identify and eliminate duplicate welfare beneficiaries across multiple government databases without exposing citizens' personal data.

Millions of Indians benefit from welfare schemes managed by various ministries and state departments, but the prevalence of duplicate and fraudulent entries leads to resource leakage, delays, and exclusion of genuine beneficiaries. This issue affects departments such as Social Justice, Rural Development, and Food & Public Distribution, and directly links to SDG 16 (Peace, Justice, and Strong Institutions) and MeitY’s digital governance mandate.

The proposed solution is a privacy-preserving, federated de-duplication system that enables secure matching of beneficiary records across databases (such as PDS, PM-KISAN, and pensions) without sharing raw personal identifiers. The platform will use cryptographic techniques like secure multi-party computation and privacy-preserving record linkage, leveraging open-source Indian digital public infrastructure where available.

Key features include: (1) a secure API for institutions to submit hashed or tokenized identifiers, (2) a deduplication engine that identifies likely duplicates without revealing sensitive data, (3) an admin dashboard for review and action, (4) open integration with mock DPI and Aadhaar-free datasets, and (5) an audit trail ensuring transparency. The working prototype should demonstrate integration with at least two mock or open government beneficiary datasets.

The platform will help reduce fraud and exclusion, ensuring more efficient use of public funds and improving trust in welfare delivery. If successful, the approach can be scaled to state or national levels, with measurable impact in savings, coverage, and data privacy compliance.