Anomaly Detection in Time Series Data for Cyber Security: Integrating Supervised, Semi-supervised and Unsupervised Methods

Authors

Claire Howard (ORCID: https://orcid.org/0000-0002-2806-9144)
Tamaramiebi K. Waidor
L Omamoke

Institutions

University of Africa (ZM)

Publication Details

Published: 2025-06-12
DOI: https://doi.org/10.56557/ajpam/2025/v7i1201
Primary Topic: Anomaly Detection Techniques and Applications
Type: article
Field-Weighted Citation Impact: 0.00

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article

Anomaly Detection in Time Series Data for Cyber Security: Integrating Supervised, Semi-supervised and Unsupervised Methods

Claire Howard, Tamaramiebi K. Waidor, L Omamoke

Jun 12, 2025

Anomaly Detection Techniques and Applications

article

Anomaly Detection in Time Series Data for Cyber Security: Integrating Supervised, Semi-supervised and Unsupervised Methods

Claire Howard, Tamaramiebi K. Waidor, L Omamoke

June 12, 2025article en

Abstract

No abstract available for this paper.

Vol. 7(1)

University of Africa (ZM)

Openalex Percentile: Top 93%

Anomaly Detection Techniques and Applications

DOI Source OpenAlex

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Anomaly Detection in Time Series Data for Cyber Security: Integrating Supervised, Semi-supervised and Unsupervised Methods — Claire Howard, Tamaramiebi K. Waidor, et al. · (2025) | TGRS Research Map | TGRS