A copula based approach for measurement validity verification in wireless sensor networks

Sanaa Kawther Ghalem; Bouabdellah Kechar; Ahcène Bounceur; Reinhardt Euler; Mohammad Hammoudeh; Farid Lalem

doi:10.1145/3018896.3065829

A copula based approach for measurement validity verification in wireless sensor networks

Sanaa Kawther Ghalem
, Bouabdellah Kechar
, Ahcène Bounceur
, Reinhardt Euler
, Mohammad Hammoudeh
, Farid Lalem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the dened data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90% and an error rate of 0.87%.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017
Editors	Hani Hamdan, Djallel Eddine Boubiche, Faouzi Hidoussi
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450347747
DOIs	https://doi.org/10.1145/3018896.3065829
State	Published - 22 Mar 2017
Externally published	Yes

Publication series

Name	ACM International Conference Proceeding Series

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Keywords

Copula
Dependency
Outlier
Reliability
Statistical
WSN

ASJC Scopus subject areas

Software
Human-Computer Interaction
Computer Vision and Pattern Recognition
Computer Networks and Communications

Access to Document

10.1145/3018896.3065829

Cite this

Ghalem, S. K., Kechar, B., Bounceur, A., Euler, R., Hammoudeh, M., & Lalem, F. (2017). A copula based approach for measurement validity verification in wireless sensor networks. In H. Hamdan, D. E. Boubiche, & F. Hidoussi (Eds.), Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017 Article a199 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3018896.3065829

Ghalem, Sanaa Kawther ; Kechar, Bouabdellah ; Bounceur, Ahcène et al. / A copula based approach for measurement validity verification in wireless sensor networks. Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017. editor / Hani Hamdan ; Djallel Eddine Boubiche ; Faouzi Hidoussi. Association for Computing Machinery, 2017. (ACM International Conference Proceeding Series).

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title = "A copula based approach for measurement validity verification in wireless sensor networks",

abstract = "Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the dened data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90\% and an error rate of 0.87\%.",

keywords = "Copula, Dependency, Outlier, Reliability, Statistical, WSN",

author = "Ghalem, \{Sanaa Kawther\} and Bouabdellah Kechar and Ahc{\`e}ne Bounceur and Reinhardt Euler and Mohammad Hammoudeh and Farid Lalem",

note = "Publisher Copyright: {\textcopyright} 2017 ACM.",

year = "2017",

month = mar,

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doi = "10.1145/3018896.3065829",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

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Ghalem, SK, Kechar, B, Bounceur, A, Euler, R, Hammoudeh, M & Lalem, F 2017, A copula based approach for measurement validity verification in wireless sensor networks. in H Hamdan, DE Boubiche & F Hidoussi (eds), Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017., a199, ACM International Conference Proceeding Series, Association for Computing Machinery. https://doi.org/10.1145/3018896.3065829

A copula based approach for measurement validity verification in wireless sensor networks. / Ghalem, Sanaa Kawther; Kechar, Bouabdellah; Bounceur, Ahcène et al.
Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017. ed. / Hani Hamdan; Djallel Eddine Boubiche; Faouzi Hidoussi. Association for Computing Machinery, 2017. a199 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A copula based approach for measurement validity verification in wireless sensor networks

AU - Ghalem, Sanaa Kawther

AU - Kechar, Bouabdellah

AU - Bounceur, Ahcène

AU - Euler, Reinhardt

AU - Hammoudeh, Mohammad

AU - Lalem, Farid

PY - 2017/3/22

Y1 - 2017/3/22

N2 - Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the dened data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90% and an error rate of 0.87%.

AB - Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the dened data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90% and an error rate of 0.87%.

KW - Copula

KW - Dependency

KW - Outlier

KW - Reliability

KW - Statistical

KW - WSN

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M3 - Conference contribution

AN - SCOPUS:85044666577

T3 - ACM International Conference Proceeding Series

BT - Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017

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Ghalem SK, Kechar B, Bounceur A, Euler R, Hammoudeh M, Lalem F. A copula based approach for measurement validity verification in wireless sensor networks. In Hamdan H, Boubiche DE, Hidoussi F, editors, Proceedings of the 2nd International Conference on Internet of Things and Cloud Computing, ICC 2017. Association for Computing Machinery. 2017. a199. (ACM International Conference Proceeding Series). doi: 10.1145/3018896.3065829

A copula based approach for measurement validity verification in wireless sensor networks

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this