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KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
Vertical Federated Learning (VFL) is a category of Federated Learning in which models are trained collaboratively among parties with vertically partitioned data.
A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
The novel Internet of Things (IoT) paradigm is composed of a growing number of heterogeneous smart objects and services that are transforming architectures and applications, increasing systems' complexity, and the need for reliability and autonomy.
Privacy-Preserving in Blockchain-based Federated Learning Systems
Federated Learning (FL) has recently arisen as a revolutionary approach to collaborative training Machine Learning models.
A Novel IoT Trust Model Leveraging Fully Distributed Behavioral Fingerprinting and Secure Delegation
With the number of connected smart devices expected to constantly grow in the next years, Internet of Things (IoT) solutions are experimenting a booming demand to make data collection and processing easier.
