Support vector machine for network intrusion and cyber-attack detection

Support vector machine for network intrusion and cyber-attack detection

Cyber-security threats are a growing concern in networked environments. The development of Intrusion Detection Systems (IDSs) is fundamental in order to provide extra level of security. We have developed an unsupervised anomaly-based IDS that uses statistical techniques to conduct the detection proc...

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Bibliographic Details
Main Authors: Kinan Ghanem, Francisco J. Aparicio-Navarro, Kostas Kyriakopoulos, Sangarapillai Lambotharan, Jonathon Chambers
Format: Default Conference proceeding
Published: 2017
Subjects:
Mechanical engineering not elsewhere classified
Classification algorithms
Cyber security
Intrusion detection systems
Machine learning techniques
Network security
Support vector machine
SVM
Mechanical Engineering not elsewhere classified
Online Access:https://hdl.handle.net/2134/26536
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https://hdl.handle.net/2134/26536

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