Outlier Detection Techniques For Wireless Sensor Networks: A Survey

    Research output: Book/ReportReportProfessional

    168 Downloads (Pure)

    Abstract

    In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the multivariate nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a decision tree to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier degree.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherPervasive Systems (PS)
    Publication statusPublished - 6 Oct 2008

    Publication series

    NameCTIT technical report series
    PublisherCentre for Telematics and Information Technology, University of Twente
    No.Supplement/TR-CTIT-08-59
    ISSN (Print)1381-3625

    Keywords

    • METIS-251217
    • EWI-13561
    • IR-65024

    Cite this

    Zhang, Y., Meratnia, N., & Havinga, P. J. M. (2008). Outlier Detection Techniques For Wireless Sensor Networks: A Survey. (CTIT technical report series; No. Supplement/TR-CTIT-08-59). Enschede: Pervasive Systems (PS).
    Zhang, Y. ; Meratnia, Nirvana ; Havinga, Paul J.M. / Outlier Detection Techniques For Wireless Sensor Networks: A Survey. Enschede : Pervasive Systems (PS), 2008. (CTIT technical report series; Supplement/TR-CTIT-08-59).
    @book{878b637dd0a542c58120b41dae07522a,
    title = "Outlier Detection Techniques For Wireless Sensor Networks: A Survey",
    abstract = "In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the multivariate nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a decision tree to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier degree.",
    keywords = "METIS-251217, EWI-13561, IR-65024",
    author = "Y. Zhang and Nirvana Meratnia and Havinga, {Paul J.M.}",
    note = "eemcs-eprint-13561",
    year = "2008",
    month = "10",
    day = "6",
    language = "Undefined",
    series = "CTIT technical report series",
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    Zhang, Y, Meratnia, N & Havinga, PJM 2008, Outlier Detection Techniques For Wireless Sensor Networks: A Survey. CTIT technical report series, no. Supplement/TR-CTIT-08-59, Pervasive Systems (PS), Enschede.

    Outlier Detection Techniques For Wireless Sensor Networks: A Survey. / Zhang, Y.; Meratnia, Nirvana; Havinga, Paul J.M.

    Enschede : Pervasive Systems (PS), 2008. (CTIT technical report series; No. Supplement/TR-CTIT-08-59).

    Research output: Book/ReportReportProfessional

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    AU - Meratnia, Nirvana

    AU - Havinga, Paul J.M.

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    N2 - In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the multivariate nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a decision tree to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier degree.

    AB - In the field of wireless sensor networks, measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the multivariate nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a decision tree to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier degree.

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    KW - EWI-13561

    KW - IR-65024

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    Zhang Y, Meratnia N, Havinga PJM. Outlier Detection Techniques For Wireless Sensor Networks: A Survey. Enschede: Pervasive Systems (PS), 2008. (CTIT technical report series; Supplement/TR-CTIT-08-59).