A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection

A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection

Abstract Intrusion detection systems (IDS) can play a significant role in detecting security threats or malicious attacks that aim to steal information and/or corrupt network protocols. To deal with the dynamic and complex nature of cyber-attacks, advanced intelligent tools have been applied resulti...

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Bibliographic Details
Main Authors: Serafeim Moustakidis, Patrik Karlsson
Format: Article
Language:English
Published: SpringerOpen 2020-08-01
Series:Cybersecurity
Subjects:
Feature extraction
Siamese convolutional neural networks
Machine learning
Intrusion detection
Online Access:http://link.springer.com/article/10.1186/s42400-020-00056-4

Internet

http://link.springer.com/article/10.1186/s42400-020-00056-4

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