scholarly journals Learning Multilevel Auto-Encoders for DDoS Attack Detection in Smart Grid Network

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 108647-108659 ◽  
Author(s):  
Shan Ali ◽  
Yuancheng Li
Keyword(s):  
Smart Grid ◽  
Attack Detection ◽  
Grid Network ◽  
Ddos Attack ◽  
Smart Grid Network ◽  
Ddos Attack Detection

An Improved DDoS Attack Detection Model Based on Unsupervised Learning in Smart Grid

2021 ◽  
pp. 550-562
Author(s):  
Zhili Ma ◽  
Hongzhong Ma ◽  
Xiang Gao ◽  
Jiyang Gai ◽  
Xuejun Zhang ◽  
...  
Keyword(s):  
Smart Grid ◽  
Unsupervised Learning ◽  
Attack Detection ◽  
Detection Model ◽  
Ddos Attack ◽  
Model Based ◽  
Ddos Attack Detection

scholarly journals A cooperative DDoS attack detection scheme based on entropy and ensemble learning in SDN

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Shanshan Yu ◽  
Jicheng Zhang ◽  
Ju Liu ◽  
Xiaoqing Zhang ◽  
Yafeng Li ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Denial Of Service ◽  
Attack Detection ◽  
Coarse Grained ◽  
Communication Overhead ◽  
Detection Scheme ◽  
Fine Grained ◽  
Ddos Attack ◽  
Network Status ◽  
Ddos Attack Detection

AbstractIn order to solve the problem of distributed denial of service (DDoS) attack detection in software-defined network, we proposed a cooperative DDoS attack detection scheme based on entropy and ensemble learning. This method sets up a coarse-grained preliminary detection module based on entropy in the edge switch to monitor the network status in real time and report to the controller if any abnormality is found. Simultaneously, a fine-grained precise attack detection module is designed in the controller, and a ensemble learning-based algorithm is utilized to further identify abnormal traffic accurately. In this framework, the idle computing capability of edge switches is fully utilized with the design idea of edge computing to offload part of the detection task from the control plane to the data plane innovatively. Simulation results of two common DDoS attack methods, ICMP and SYN, show that the system can effectively detect DDoS attacks and greatly reduce the southbound communication overhead and the burden of the controller as well as the detection delay of the attacks.

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