Privacy-Preserving Delegation Of Decision Tree Classification
2020 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TAIWAN)(2020)
摘要
In the era of cloud computing with security, how to outsource a trained model to the server but preserve the model privacy is a significant problem for decision tree classification (DTC). In this paper, we aim for constructing an interactive system to realize privacy-preserving delegation for DTC. We focus on a basic structure of DTC, and believe that it can be generalization. The main technique to preserve privacy is to build secret sharing-based protocols for the model owner, user, and server. However, to overcome communication issues between the model owner and user, we achieve compression by using pseudorandom generators.
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关键词
Privacy-preserving delegation, decision tree classification, secret sharing, security
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