Secure Two-Party Feature Selection

2019/01/03 by Vanishree Rao, Yunhui Long, Rao, Vanishree +9 · 1 citation
Computer Science · #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Internet Traffic Analysis and Secure E-voting #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.1901.00832

openalex publication_date 2019/01/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this work, we study how to securely evaluate the value of trading data without requiring a trusted third party. We focus on the important machine learning task of classification. This leads us to propose a provably secure four-round protocol that computes the value of the data to be traded without revealing the data to the potential acquirer. The theoretical results demonstrate a number of important properties of the proposed protocol. In particular, we prove the security of the proposed protocol in the honest-but-curious adversary model.

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