PIVODL: Privacy-Preserving Vertical Federated Learning Over Distributed Labels

Federated learning (FL) is an emerging privacy preserving machine learning protocol that allows multiple devices to collaboratively train a shared global model without revealing their private local data. Nonparametric models like gradient boosting decision trees (GBDTs) have been commonly used in FL for vertically partitioned data. However,...

ROSE: Robust Searchable Encryption with Forward and Backward Security

Dynamic searchable symmetric encryption (DSSE) has been widely recognized as a promising technique to delegate update and search queries over an outsourced database to an untrusted server while guaranteeing the privacy of data. Many efforts on DSSE have been devoted to obtaining a good tradeoff between security and performance. However, it...

DEKS: A Secure Cloud-Based Searchable Service Can Make Attackers Pay

Many practical secure systems have been designed to prevent real-world attacks via maximizing the attacking cost so as to reduce attack intentions. Inspired by this philosophy, we propose a new concept named delay encryption with keyword search (DEKS) to resist the notorious keyword guessing attack (KGA), in the context of secure cloud-based...