49 天前 - … power Internet of Things and higher requirements for grid security protection.
Distributed … proposes an innovative two-stage anomaly detection method based on graph neural …

86 天前 - … techniques are autoencoders and graph neural networks (GNNs).Auto encoders are
a type of neural network … GNNs can be used to learn pattern in the data thatare distributed …

90 天前 - … Process mining started in the late 1990-ties and initially … Directly-Follows Graphs
(DFGs) or Petri nets describing the … such as process mining, clickstream analytics, IoT analytics, …

99 天前 - … anomaly detection framework based on Continuous Temporal Graph (CTG) neural
network … achieved by the traditional DL methods on the TON-IoT dataset may be attributable …

174 天前 - … Introduction With the rapid development of mobile Internet, smartphones and IoT …
Then, we count the number of these tokens each encoder generates and plot the distribution in …

182 天前 - This Special Issue sheds light on the escalating significance of intelligent data analysis
and its applications in the era of burgeoning big data. It has emerged as a pivotal driver …

191 天前 - … follows: Blockchain and Distributed Systems; Network Security and Privacy Protection;
… and Encryption Techniques; Machine Learning and Security; and Internet of Things and …

208 天前 - … In the face of anomaly detection algorithms for multi-… the IoT monitoring system,
the currently popular method is to implement a model based on the graph neural network (GNN). …

210 天前 - … anomaly detection method relies on a variant of GNNs known as Graph Convolutional
Neural Networks (… graph neural networks with a semantic math parser for iot systems,” …

265 天前 - … In addition, special thanks are due to the members of the International Program
Committee and the external reviewers for a rigorous and robust reviewing process. We are also …