Yantai University

Benquan Chen

Zhaowei Liu

Peng Wang

Tengjiang Wang

Xinxin Zhao

Wenhan Hou

Hongwei Dai

Yingying Sun

Zhizhong Liu

Yanle Liu

Rufei Gao

Zhifei Lu

The present invention belongs to the technical field of data security of industrial Internet, and provides a method and system for detecting abnormal nodes in industrial Internet, a medium and a device. In the industrial Internet, different data holders firstly transform their own local node data into graphic data. Before local model training, the data holders firstly use a spectral clustering algorithm to perform certain clustering operations on local data, cluster the node data of the same category into the same cluster, and then perform local model training on a clustered result to obtain partial aggregation features. The trained partial features are uploaded to a trusted third-party server for global feature aggregation. Through an attention mechanism, different weights are assigned for partial features uploaded by different data holders, and the aggregated global features are delivered to each data holder for a new round of training.

Method and system for detecting abnormal nodes in industrial internet, and medium and device

Growing community of inventors

Yantai, China

Benquan Chen