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https://doi.org/10.21256/zhaw-28240| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | AIDA : analytic isolation and distance-based anomaly detection algorithm |
| Autor/-in: | Souto Arias, Luis Antonio Oosterlee, Cornelis W. Cirillo, Pasquale |
| et. al: | No |
| DOI: | 10.1016/j.patcog.2023.109607 10.21256/zhaw-28240 |
| Erschienen in: | Pattern Recognition |
| Band(Heft): | 141 |
| Heft: | 109607 |
| Erscheinungsdatum: | 2023 |
| Verlag / Hrsg. Institution: | Elsevier |
| ISSN: | 0031-3203 1873-5142 |
| Sprache: | Englisch |
| Schlagwörter: | Anomaly explanation; Distance; Ensemble method; Isolation; Outlier detection |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren |
| Zusammenfassung: | Many unsupervised anomaly detection algorithms rely on the concept of nearest neighbours to compute the anomaly scores. Such algorithms are popular because there are no assumptions about the data, making them a robust choice for unstructured datasets. However, the number (k) of nearest neighbours, which critically affects the model performance, cannot be tuned in an unsupervised setting. Hence, we propose the new and parameter-free Analytic Isolation and Distance-based Anomaly (AIDA) detection algorithm, that combines the metrics of distance with isolation. Based on AIDA, we also introduce the Tempered Isolation-based eXplanation (TIX) algorithm, which identifies the most relevant features characterizing an outlier, even in large multi-dimensional datasets, improving the overall explainability of the detection mechanism. Both AIDA and TIX are thoroughly tested and compared with state-of-the-art alternatives, proving to be useful additions to the existing set of tools in anomaly detection. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/28240 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Management and Law |
| Organisationseinheit: | Institut für Wirtschaftsinformatik (IWI) |
| Enthalten in den Sammlungen: | Publikationen School of Management and Law |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2023_SoutoArias-etal_AIDA-Analytic-isolation-and-distance-based-anomaly-detection-algorithm.pdf | 1.9 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Souto Arias, L. A., Oosterlee, C. W., & Cirillo, P. (2023). AIDA : analytic isolation and distance-based anomaly detection algorithm. Pattern Recognition, 141(109607). https://doi.org/10.1016/j.patcog.2023.109607
Souto Arias, L.A., Oosterlee, C.W. and Cirillo, P. (2023) ‘AIDA : analytic isolation and distance-based anomaly detection algorithm’, Pattern Recognition, 141(109607). Available at: https://doi.org/10.1016/j.patcog.2023.109607.
L. A. Souto Arias, C. W. Oosterlee, and P. Cirillo, “AIDA : analytic isolation and distance-based anomaly detection algorithm,” Pattern Recognition, vol. 141, no. 109607, 2023, doi: 10.1016/j.patcog.2023.109607.
SOUTO ARIAS, Luis Antonio, Cornelis W. OOSTERLEE und Pasquale CIRILLO, 2023. AIDA : analytic isolation and distance-based anomaly detection algorithm. Pattern Recognition. 2023. Bd. 141, Nr. 109607. DOI 10.1016/j.patcog.2023.109607
Souto Arias, Luis Antonio, Cornelis W. Oosterlee, and Pasquale Cirillo. 2023. “AIDA : Analytic Isolation and Distance-Based Anomaly Detection Algorithm.” Pattern Recognition 141 (109607). https://doi.org/10.1016/j.patcog.2023.109607.
Souto Arias, Luis Antonio, et al. “AIDA : Analytic Isolation and Distance-Based Anomaly Detection Algorithm.” Pattern Recognition, vol. 141, no. 109607, 2023, https://doi.org/10.1016/j.patcog.2023.109607.
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