research-article

Elliptical anomalies in wireless sensor networks

Authors:

Sutharshan Rajasegarar,

James C. Bezdek,

Christopher Leckie,

Marimuthu PalaniswamiAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 6, Issue 1

Article No.: 7, Pages 1 - 28

https://doi.org/10.1145/1653760.1653767

Published: 05 January 2010 Publication History

Abstract

Anomalies in wireless sensor networks can occur due to malicious attacks, faulty sensors, changes in the observed external phenomena, or errors in communication. Defining and detecting these interesting events in energy-constrained situations is an important task in managing these types of networks. A key challenge is how to detect anomalies with few false alarms while preserving the limited energy in the network. In this article, we define different types of anomalies that occur in wireless sensor networks and provide formal models for them. We illustrate the model using statistical parameters on a dataset gathered from a real wireless sensor network deployment at the Intel Berkeley Research Laboratory. Our experiments with a novel distributed anomaly detection algorithm show that it can detect elliptical anomalies with exactly the same accuracy as that of a centralized scheme, while achieving a significant reduction in energy consumption in the network. Finally, we demonstrate that our model compares favorably to four other well-known schemes on four datasets.

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Yue WChen LHuang H(2023)Research on Machine Learning Algorithm-Based Approach for Detecting Abnormal Data from Environmental Sensors in Different DimensionsProceedings of the 2023 International Joint Conference on Robotics and Artificial Intelligence10.1145/3632971.3632990(26-33)Online publication date: 7-Jul-2023
https://dl.acm.org/doi/10.1145/3632971.3632990
Mirzaie SAvazAghaei MBushehrian O(2021)Anomaly Detection in Urban Water Distribution Grids Using Fog Computing Architecture2021 29th Iranian Conference on Electrical Engineering (ICEE)10.1109/ICEE52715.2021.9544486(591-595)Online publication date: 18-May-2021
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Safaei MAsadi SDriss MBoulila WAlsaeedi AChizari HAbdullah RSafaei M(2020)A Systematic Literature Review on Outlier Detection in Wireless Sensor NetworksSymmetry10.3390/sym1203032812:3(328)Online publication date: 25-Feb-2020
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Index Terms

Elliptical anomalies in wireless sensor networks
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Networks
  1. Network architectures
  2. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 6, Issue 1

December 2009

258 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1653760

Issue’s Table of Contents

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 05 January 2010

Accepted: 01 December 2008

Revised: 01 December 2008

Received: 01 October 2007

Published in TOSN Volume 6, Issue 1

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Cited By

Yue WChen LHuang H(2023)Research on Machine Learning Algorithm-Based Approach for Detecting Abnormal Data from Environmental Sensors in Different DimensionsProceedings of the 2023 International Joint Conference on Robotics and Artificial Intelligence10.1145/3632971.3632990(26-33)Online publication date: 7-Jul-2023
https://dl.acm.org/doi/10.1145/3632971.3632990
Mirzaie SAvazAghaei MBushehrian O(2021)Anomaly Detection in Urban Water Distribution Grids Using Fog Computing Architecture2021 29th Iranian Conference on Electrical Engineering (ICEE)10.1109/ICEE52715.2021.9544486(591-595)Online publication date: 18-May-2021
https://doi.org/10.1109/ICEE52715.2021.9544486
Safaei MAsadi SDriss MBoulila WAlsaeedi AChizari HAbdullah RSafaei M(2020)A Systematic Literature Review on Outlier Detection in Wireless Sensor NetworksSymmetry10.3390/sym1203032812:3(328)Online publication date: 25-Feb-2020
https://doi.org/10.3390/sym12030328
Reunanen NRäty TLintonen T(2020)Automatic optimization of outlier detection ensembles using a limited number of outlier examplesInternational Journal of Data Science and Analytics10.1007/s41060-020-00222-4Online publication date: 8-Jun-2020
https://doi.org/10.1007/s41060-020-00222-4
Zamini MHasheminejad S(2019)A comprehensive survey of anomaly detection in banking, wireless sensor networks, social networks, and healthcareIntelligent Decision Technologies10.3233/IDT-17015513:2(229-270)Online publication date: 17-May-2019
https://doi.org/10.3233/IDT-170155
(2018)A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifierInternational Journal of Sensor Networks10.5555/3272279.327228527:3(200-214)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.5555/3272279.3272285
(2018)A distributed anomaly detection model for wireless sensor networks based on the one?class principal component classifierInternational Journal of Sensor Networks10.5555/3272272.327227827:3(200-214)Online publication date: 1-Jan-2018
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Minhas UNaqvi IQaisar SAli KShahid SAslam M(2018)A WSN for Monitoring and Event Reporting in Underground Mine EnvironmentsIEEE Systems Journal10.1109/JSYST.2016.264410912:1(485-496)Online publication date: Mar-2018
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Chenaghlou MMoshtaghi MLeckie CSalehi M(2018)Online Clustering for Evolving Data Streams with Online Anomaly DetectionAdvances in Knowledge Discovery and Data Mining10.1007/978-3-319-93037-4_40(508-521)Online publication date: 3-Jun-2018
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