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Authors: Van-Khoa Le ; Edith Grall-Maes and Pierre Beauseroy

Affiliation: Troyes University of Technology, France

ISBN: 978-989-758-276-9

Keyword(s): Anomaly Detection, Statistic Method, Security System, Cyber-physical Attacks, Key Metric.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Classification ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; Image and Video Analysis ; Pattern Recognition ; Signal Processing ; Software Engineering ; Theory and Methods ; Video Analysis

Abstract: This paper presents a detection process which utilizes various sensors (camera, card readers, movement detector) for detecting automatically abnormal events. The detection process strengthens current security systems to identify attackers in the context of building and office. Key metrics are proposed to describe people’s behavior in critical zones of the building. They are built using measures from the sensors, which provide information about the person, the position, and the instant. These metrics are used to classify abnormal behaviors from regular ones, based on a statistical classifier. This technique is tested on both simulated data and real data, in which an attacking scenario was prepared by security experts. Results show that abnormal events from the scenario have been successfully detected. The experiments demonstrate that the proposed key metrics are relevant and the proposed detection scheme is appropriate for infrastructure surveillance.

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Paper citation in several formats:
Le, V.; Grall-Maes, E. and Beauseroy, P. (2018). Abnormal Events Detection for Infrastructure Security using Key Metrics.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 284-290. DOI: 10.5220/0006552102840290

@conference{icpram18,
author={Van{-}Khoa Le. and Edith Grall{-}Maes. and Pierre Beauseroy.},
title={Abnormal Events Detection for Infrastructure Security using Key Metrics},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={284-290},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006552102840290},
isbn={978-989-758-276-9},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Abnormal Events Detection for Infrastructure Security using Key Metrics
SN - 978-989-758-276-9
AU - Le, V.
AU - Grall-Maes, E.
AU - Beauseroy, P.
PY - 2018
SP - 284
EP - 290
DO - 10.5220/0006552102840290

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