Log-Based Anomaly Detection Without Ground-Truth: Evaluating Weakly Supervised, Semi-Supervised, and Unsupervised Deep Learning Approaches

Nadira Anjum Nipa; Nizar Bouguila; Zachary Patterson

doi:10.1109/isie62713.2025.11124715

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Log-Based Anomaly Detection Without Ground-Truth: Evaluating Weakly Supervised, Semi-Supervised, and Unsupervised Deep Learning Approaches

Nadira Anjum Nipa Nizar Bouguila Zachary Patterson

Year: 2025 Pages: 1-8

DOI: 10.1109/isie62713.2025.11124715

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Keywords:

Ground truth Anomaly detection Artificial intelligence Computer science Supervised learning Pattern recognition (psychology) Unsupervised learning Anomaly (physics) Deep learning Semi-supervised learning Machine learning Artificial neural network Physics

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Data-Driven Disease Surveillance

Health Sciences → Medicine → Epidemiology

Log-Based Anomaly Detection Without Ground-Truth: Evaluating Weakly Supervised, Semi-Supervised, and Unsupervised Deep Learning Approaches

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