Etcnlog: a system log anomaly detection method based on efficient channel attention and temporal convolutional network

HIGHLIGHTS

• who: Yuyuan Chang and collaborators from the College of Information Science and Engineering, Xinjiang University, Urumqi, China have published the article: ETCNLog: A System Log Anomaly Detection Method Based on Efficient Channel Attention and Temporal Convolutional Network, in the Journal: Electronics 2023, 12, 1877. of /2023/
• what: If a new log does not follow the rules the model has learned, it is considered an anomaly. The authors propose a novel method, ETCNLog, to handle a longer sequence log. The authors propose an anomaly detection model based on ECA and a TCN to mine longterm dependencies . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.