Minoru Kawahara
1 indexed paper
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126
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Crypto×1
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2026
Privacy-Preserving Product-Quantized Approximate Nearest Neighbor Search Framework for Large-scale Datasets via A Hybrid of Fully Homomorphic Encryption and Trusted Execution Environment
The paper proposes a Privacy-Preserving Product-Quantization Approximate Nearest Neighbor (PPPQ-ANN) framework that achieves practical performance and strong privacy guarantees for large-scale nearest-neighbor searches by hybridizing Fully Homomorphic Encryption (FHE) and Trusted Execution Environment (TEE).
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