CRApr 9

xDup: Privacy-Preserving Deduplication for Humanitarian Organizations using Fuzzy PSI

arXiv:2604.0801923.5h-index: 15
AI Analysis

This addresses privacy risks for vulnerable aid recipients in humanitarian missions, offering a practical improvement over existing methods.

The paper tackles the problem of privacy-preserving deduplication for humanitarian organizations to prevent duplicate aid distribution, presenting xDup, a system that is two orders of magnitude faster than current solutions.

Humanitarian organizations help to ensure people's livelihoods in crisis situations. Typically, multiple organizations operate in the same region. To ensure that the limited budget of these organizations can help as many people as possible, organizations perform cross-organizational deduplication to detect duplicate registrations and ensure recipients receive aid from at most one organization. Current deduplication approaches risk privacy harm to vulnerable aid recipients by sharing their data with other organizations. We analyzed the needs of humanitarian organizations to identify the requirements for privacy-friendly cross-organizational deduplication fit for real-life humanitarian missions. We present xDup, a new practical deduplication system that meets the requirements of humanitarian organizations and is two orders of magnitude faster than current solutions. xDup builds on Fuzzy PSI, and we present otFPSI, a concretely efficient Fuzzy PSI protocol for Hamming Space without input assumptions. We show that it is more efficient than existing Fuzzy PSI protocols.

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