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An Improved Distributed PCA-Based Outlier Detection in Wireless Sensor Network

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11067))

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Abstract

Outlier detection in wireless sensor networks (WSNs) is essential to ensure data quality, secure monitoring and reliable detection of interesting and critical events. Principal Components Analysis (PCA) has attracted a great interest in the machine learning field especially in outlier detection in WSNs. An efficient and effective method called Improved Distributed PCA-Based Outlier Detection (IDPCA) has been proposed in this paper. The proposed scheme operates on each sensor node respectively, thus reducing the communication cost and prolonging the lifetime of the network. Through taking advantage of the data spatial correlation of adjacent nodes, the proposal can significantly reduce the false alarm rate and distinguish events and errors in real time. Experiments with both synthetic and the real data collected from the Intel Berkeley Research Laboratory indicate that IDPCA achieves a higher detection rate with a lower false alarm rate, while reducing the communication overhead than previous methods.

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Acknowledgments

This work is sponsored by The National Natural Science Foundation of China for Youth (Grant No. 61602263, No. 61572263), The Natural Science Foundation of Jiangsu Province, China (Grant No. BK20160916, No. BK20151507), The National post-doctoral fund (Grant No. 2017M621798), The NUPTSF (Grant No. NY216020).

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China

    Wentian Zheng

  2. College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China

    Lijun Yang

  3. College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China

    Meng Wu

Authors
  1. Wentian Zheng
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  2. Lijun Yang
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  3. Meng Wu
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Corresponding author

Correspondence to Lijun Yang .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zheng, W., Yang, L., Wu, M. (2018). An Improved Distributed PCA-Based Outlier Detection in Wireless Sensor Network. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11067. Springer, Cham. https://doi.org/10.1007/978-3-030-00018-9_4

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  • DOI: https://doi.org/10.1007/978-3-030-00018-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00017-2

  • Online ISBN: 978-3-030-00018-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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