Title: Survey of Privacy Threats and Countermeasures in Federated Learning Show Chinese title

Title: 联邦学习中的隐私威胁与对策综述

Abstract: Federated learning is widely considered to be as a privacy-aware learning method because no training data is exchanged directly between clients. Nevertheless, there are threats to privacy in federated learning, and privacy countermeasures have been studied. However, we note that common and unique privacy threats among typical types of federated learning have not been categorized and described in a comprehensive and specific way. In this paper, we describe privacy threats and countermeasures for the typical types of federated learning; horizontal federated learning, vertical federated learning, and transfer federated learning. Show Chinese abstract

Abstract: 联邦学习被广泛认为是一种隐私感知的学习方法，因为客户端之间不直接交换训练数据。 然而，联邦学习中存在隐私威胁，已经对隐私对策进行了研究。 然而，我们注意到，典型类型的联邦学习中的常见和独特隐私威胁尚未以全面且具体的方式进行分类和描述。 在本文中，我们描述了典型类型的联邦学习的隐私威胁和对策；横向联邦学习、纵向联邦学习和迁移联邦学习。