Deep Reinforcement Learning-Based Traffic Sampling for Multiple Traffic Analyzers on Software-Defined Networks

Deep Reinforcement Learning-Based Traffic Sampling for Multiple Traffic Analyzers on Software-Defined Networks

Intrusion detection system (IDS) and deep packet inspection (DPI) are widely used to detect network attacks and anomalies, thereby enhancing cyber-security. Conventional traffic analyzers such as IDS have fixed locations and a limited capacity to perform DPI on large volumes of network traffic. Nowa...

Full description

Bibliographic Details
Main Authors: Sunghwan Kim, Seunghyun Yoon, Hyuk Lim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Cyber-security
network traffic monitoring
intrusion detection system
software-defined networking
deep reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/9385142/

Internet

https://ieeexplore.ieee.org/document/9385142/

Similar Items