Tensor-based anomaly detection: An interdisciplinary survey

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Fanaee T, H (Author) Other; João Gama (Author) FEP

Journal

Title: Knowledge-Based Systems

Vol. 98

Pages: 130-147

ISSN: 0950-7051

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 110 Citations

Scopus - 129 Citations

Other information

Authenticus ID: P-00K-7MR

DOI: 10.1016/j.knosys.2016.01.027

Abstract (EN): Traditional spectral-based methods such as PCA are popular for anomaly detection in a variety of problems and domains. However, if data includes tensor (multiway) structure (e.g. space-time-measurements), some meaningful anomalies may remain invisible with these methods. Although tensor-based anomaly detection (TAD) has been applied within a variety of disciplines over the last twenty years, it is not yet recognized as a formal category in anomaly detection. This survey aims to highlight the potential of tensor-based techniques as a novel approach for detection and identification of abnormalities and failures. We survey the interdisciplinary works in which TAD is reported and characterize the learning strategies, methods and applications; extract the important open issues in TAD and provide the corresponding existing solutions according to the state-of-the-art.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18