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.
翻译:在这项工作中,我们研究如何在不要求受信任的第三方的情况下安全地评估贸易数据的价值。我们侧重于重要的机器学习分类任务。这导致我们提出一个可以证明安全的四轮协议,在计算拟交易数据的价值时不向潜在获取者披露数据。理论结果显示了拟议议定书的若干重要特性。特别是,我们证明拟议议定书在诚实但有争议对抗模式中的安全。