Chen Wang1, Jian Xu1,*, Jiarun Li1, Yan Dong1, Nitin Naik2
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1421-1436, 2023, DOI:10.32604/iasc.2023.034123
Abstract Outsourcing the k-Nearest Neighbor (kNN) classifier to the cloud is useful, yet it will lead to serious privacy leakage due to sensitive outsourced data and models. In this paper, we design, implement and evaluate a new system employing an outsourced privacy-preserving kNN Classifier Model based on Multi-Key Homomorphic Encryption (kNNCM-MKHE). We firstly propose a security protocol based on Multi-key Brakerski-Gentry-Vaikuntanathan (BGV) for collaborative evaluation of the kNN classifier provided by multiple model owners. Analyze the operations of kNN and extract basic operations, such as addition, multiplication, and comparison. It supports the computation of encrypted data with different public keys. At… More >
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