The existing wireless network intrusion detection algorithms based on supervised learning
confront many challenges, such as high false detection rate, difficulty in finding unknown …

针对物联网(IoTs) 场景下, 联邦学习(FL) 过程中大量设备节点之间因冗余的梯度交互通信而带来
的不可忽视的通信成本问题, 该文提出一种阈值自适应的梯度通信压缩机制. 首先 …

In recent years, with the rapid development of China's network scale, the frequency of power
Internet has also increased sharply. But at the same time, in the process of power grid …

As an emerging machine learning method, Federated Learning is widely used in network
anomaly detection scenarios. However, many current federated learning-based network …

Federated Learning (FL) is a newly emerged federated optimization technique for distributed
data in a federated network. The participants in FL that train the model locally are classified …

Considering the non-negligible communication cost problem caused by redundant gradient
interactive communication between a large number of device nodes in the Federated …

In response to the complex data trust evaluation process in the current process of secure
sharing of university personnel archive data, which leads to long data encryption time and …