One-pass-throw-away learning for cybersecurity in streaming non-stationary environments by dynamic stratum network.
Throughout recent times, cybersecurity problems have occurred in various business applications. Although previous researchers proposed to cope with the occurrence of cybersecurity issues, their methods repeatedly replicated the training processes for several times to classify datasets of these probl...
Main Authors: | Mongkhon Thakong, Suphakant Phimoltares, Saichon Jaiyen, Chidchanok Lursinsap |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2018-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC6126810?pdf=render |
Similar Items
-
Fast Learning and Testing for Imbalanced Multi-Class Changes in Streaming Data by Dynamic Multi-Stratum Network
by: Mongkhon Thakong, et al.
Published: (2017-01-01) -
Streaming chunk incremental learning for class-wise data stream classification with fast learning speed and low structural complexity.
by: Prem Junsawang, et al.
Published: (2019-01-01) -
Correct and stable sorting for overflow streaming data with a limited storage size and a uniprocessor
by: Suluk Chaikhan, et al.
Published: (2021-02-01) -
Neural Learning With Recoil Behavior in Hyperellipsoidal Structure
by: Kanoksilp Jindadoungrut, et al.
Published: (2020-01-01) -
Scalable Hyper-Ellipsoidal Function With Projection Ratio for Local Distributed Streaming Data Classification
by: Perasut Rungcharassang, et al.
Published: (2020-01-01)