Online Anomaly Detection for Smartphone-Based Multivariate Behavioral Time Series Data

Smartphones can be used to collect granular behavioral data unobtrusively, over long time periods, in real-world settings. To detect aberrant behaviors in large volumes of passively collected smartphone data, we propose an online anomaly detection method using Hotelling’s T-squared test. The test st...

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Detalles Bibliográficos
Autores principales: Liu, Gang, Onnela, Jukka-Pekka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8954023/
https://www.ncbi.nlm.nih.gov/pubmed/35336281
http://dx.doi.org/10.3390/s22062110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8954023/
https://www.ncbi.nlm.nih.gov/pubmed/35336281
http://dx.doi.org/10.3390/s22062110

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