Early Detection of Abnormal Attacks in Software-Defined Networking Using Machine Learning Approaches
Recent developments have made software-defined networking (SDN) a popular technology for solving the inherent problems of conventional distributed networks. The key benefit of SDN is the decoupling between the control plane and the data plane, which makes the network more flexible and easier to mana...
Main Authors: | Hsiu-Min Chuang, Fanpyn Liu, Chung-Hsien Tsai |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-06-01
|
Series: | Symmetry |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-8994/14/6/1178 |
Similar Items
-
A New Approach for Abnormal Human Activities Recognition Based on ConvLSTM Architecture
by: Roberta Vrskova, et al.
Published: (2022-04-01) -
Lightweight Model for Botnet Attack Detection in Software Defined Network-Orchestrated IoT
by: Worku Gachena Negera, et al.
Published: (2023-04-01) -
Multilabel multiclass sentiment and emotion dataset from indonesian mobile application review
by: Riccosan, et al.
Published: (2023-10-01) -
Evaluation of the Improved Extreme Learning Machine for Machine Failure Multiclass Classification
by: Nico Surantha, et al.
Published: (2023-08-01) -
A Survey on the Latest Intrusion Detection Datasets for Software Defined Networking Environments
by: Harman Yousif Ibrahim Khalid, et al.
Published: (2024-04-01)