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Big Data Security Analytic for Smart Grid with Fog Nodes

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Book cover Security, Privacy, and Anonymity in Computation, Communication, and Storage (SpaCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10066))

Abstract

Big data throws big security challenges in Smart Grid. Fog computing emerges as a novel technology to bring the ability of Cloud and big data analytic (BDA) to the edge of the networks. However, we lack practice on how to utilize Fog, Cloud, and BDA to address big data security challenges in Smart Grid. In this paper, we propose a Mapreduce-style algorithm, named Mapreduce-style Fast Non-Technical Loss Fraud Detection scheme (Mapreduce-style FNFD), to detect Non-Technical Loss fraud in Smart Grid. Compared to its original version, FNFD, Mapreduce-style FNFD can utilize the ability of Cloud, Fog, and BDA, and thus can solve big data security issues.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under the Grant 61374200, and the National Science Foundation (NSF) under Grant CNS-1059265.

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Authors and Affiliations

  1. Department of Computer Science, The University of Alabama, 342 H.M. Comer, Box 870290, Tuscaloosa, Alabama, 35487-0290, USA

    Wenlin Han & Yang Xiao

Authors
  1. Wenlin Han
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  2. Yang Xiao
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Corresponding author

Correspondence to Yang Xiao .

Editor information

Editors and Affiliations

  1. Guangzhou University, Guangzhou, China

    Guojun Wang

  2. Department of Computer Science, Colorado State University, Fort Collins, Colorado, USA

    Indrakshi Ray

  3. University of the West of Scotland, Paisley, Glasgow, United Kingdom

    Jose M. Alcaraz Calero

  4. Indian Institute of Information Technology and Management, Kerala (IIITMK), Trivandrum, Kerala, India

    Sabu M. Thampi

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Han, W., Xiao, Y. (2016). Big Data Security Analytic for Smart Grid with Fog Nodes. In: Wang, G., Ray, I., Alcaraz Calero, J., Thampi, S. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2016. Lecture Notes in Computer Science(), vol 10066. Springer, Cham. https://doi.org/10.1007/978-3-319-49148-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-49148-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49147-9

  • Online ISBN: 978-3-319-49148-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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