Did you mean: Secure and Efficient kNN Queries.
May 5, 2020 · We propose an efficient privacy-preserving query protocol to accomplish the k-nearest neighbor (k-NN) query processing on outsourced data. We ...
People also ask
What are some techniques for improving the efficiency of KNN?
How to make KNN more accurate?
How do you choose the optimal k in KNN?
What is the efficient KNN algorithm?
May 4, 2017 · [5, 14] present solutions to the problem of computing k-NN, where the data is fragmented among different parties, while also preserving privacy.
May 5, 2020 · In this article, we propose a secure and efficient distributed kNN classification algorithm (SEED-kNN) to prevent information and control flow ...
Sep 7, 2022 · ... The k-nearest neighbor (k-NN) algorithm is a simple, yet powerful, clustering technique for classification and regression problems. k-NN ...
In this paper, we focus on solving the k-nearest neighbor (kNN) query problem over encrypted database outsourced to a cloud: a user issues an encrypted query ...
In this paper, we study the problem of secure and verifiable k nearest neighbor query. (SVkNN). To support SVkNN, we first propose a novel unified structure ...
In this paper, we focus on the problem of KNN set similarity search over the encrypted datasets. We use Yao's garbled circuits and secret sharing as underlying ...
Mar 30, 2015 · A straightforward approach to this problem is to encrypt the user's query point and the entire spatial dataset using the asymmetric scalar- ...
The k-nearest neighbors (kNN) classifier predicts a class of a query, q, by taking the majority class of its k neighbors in an existing. (already classified) ...
kNN-R: Building Secure and Efficient Outsourced kNN Query. Service with the ... builds our outsourced databases to process range queries and k nearest neighbors ...