Unsupervised Anomaly Detection Approach for Cyberattack Identification

Lander Segurola-Gil; Mikel Moreno-Moreno; Itziar Irigoien; Ane M. Florez-Tapia

doi:10.1007/s13042-024-02237-w

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Unsupervised Anomaly Detection Approach for Cyberattack Identification

Lander Segurola-Gil Mikel Moreno-Moreno Itziar Irigoien Ane M. Florez-Tapia

Year: 2024 Journal: International Journal of Machine Learning and Cybernetics Vol: 15 (11)Pages: 5291-5302 Publisher: Springer Science+Business Media

DOI: 10.1007/s13042-024-02237-w

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Keywords:

Computer science Robustness (evolution) Artificial intelligence Anomaly detection Computational intelligence Unsupervised learning Machine learning Naive Bayes classifier Identification (biology) Feature selection The Internet Data mining Pattern recognition (psychology) Support vector machine

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Topics

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Unsupervised Anomaly Detection Approach for Cyberattack Identification

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