A new proposal to speed up one-class projectionist techniques

Abstract With the increasing complexity of cyber-physical systems, combined with the potential risk of cyber-attacks, the possibility of having reliable anomaly detection systems plays a significant role in every process, promoting the scientific community’s efforts. Due to the remarkable importance of this kind of tool, a wide variety of approaches and techniques model the expected behavior of a system. An intuitive way to deal with this problem consists of determining the boundaries of the dataset. This document presents a novel procedure to speed up an existing anomaly detection technique based on non-convex boundaries.

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Publication Details

Journal
Logic Journal of IGPL
Published
2025-05-21
DOI
https://doi.org/10.1093/jigpal/jzaf048
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

A new proposal to speed up one-class projectionist techniques

Álvaro Michelena, MANUEL G. PENEDO, Alejandro Vidal-Bralo, José Aveleira-Mata et al.
Logic Journal of IGPL
Anomaly Detection Techniques and Applications
article

A new proposal to speed up one-class projectionist techniques

Álvaro Michelena, MANUEL G. PENEDO, Alejandro Vidal-Bralo, José Aveleira-Mata, Esteban Jove, José-Luis Calvo-Rolle
article en

Abstract

Abstract With the increasing complexity of cyber-physical systems, combined with the potential risk of cyber-attacks, the possibility of having reliable anomaly detection systems plays a significant role in every process, promoting the scientific community’s efforts. Due to the remarkable importance of this kind of tool, a wide variety of approaches and techniques model the expected behavior of a system. An intuitive way to deal with this problem consists of determining the boundaries of the dataset. This document presents a novel procedure to speed up an existing anomaly detection technique based on non-convex boundaries.

Logic Journal of IGPLVol. 34(1)
Universidade da Coruña (ES), Universidad de León (ES)
Reduced inequalities
Openalex Percentile: Top 12%
Anomaly Detection Techniques and Applications
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