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InfoResearchPeer-reviewed
Efficient Privacy-Preserving Jaccard Similarity Evaluation Over Multisets for Secure Collaborative Data Analysis
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Summary
This paper presents a secure protocol for computing the Jaccard Coefficient over multisets, targeting collaborative data analysis and deduplication. Under the semi-honest adversarial model, the intersection and union cardinalities stay hidden from all parties, including the decryption key holder. The protocol runs at a linear cost of O(e_{m-1}) without accuracy loss, and a cloud-assisted encryption scheme improves efficiency by 25.5% to 30.4% over the non-cloud-assisted scheme.