An LSTM-Based Deep Learning Approach for Classifying Malicious Traffic at the Packet Level

An LSTM-Based Deep Learning Approach for Classifying Malicious Traffic at the Packet Level

Recently, deep learning has been successfully applied to network security assessments and intrusion detection systems (IDSs) with various breakthroughs such as using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) to classify malicious traffic. However, these state-of-the-art s...

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Bibliographic Details
Main Authors: Ren-Hung Hwang, Min-Chun Peng, Van-Linh Nguyen, Yu-Lun Chang
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Applied Sciences
Subjects:
deep learning for network security
long short-term memory
malicious traffic classification
Online Access:https://www.mdpi.com/2076-3417/9/16/3414

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