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Efficient Detection Method for Data Integrity Attacks in Smart Grid

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

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

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Abstract

With the developing of the Smart Grid, false data injection attacks (FDIAs) as a typical data integrity attack successfully bypass the traditional bad data detection and identification, has a serious influence on the power system safe and reliable operation. State estimation, which is an important process in smart grid, is used in system monitoring to get optimally estimate the power grid state through analysis of the monitoring data. However, FDIAs compromising data integrity will lead to wrong decision makings in power dispatch or electric power market transactions. In this paper, focusing on the power property, we introduce an index to quantitatively measure the node voltage stability and reflect the influence of FDIAs on the power system. Then, we use an improved clustering algorithm to identify the node vulnerability level, which helps operators take measures and detect the false data injection attacks timely. Besides, one effective state forecasting detection method is proposed, which is meaningful for real-time detection of false data injection attacks. Finally, the simulation result verifies the effectiveness and performance of the proposed method.

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Acknowledgments

This work is partially supported by Natural Science Foundation of China under grant 61402171, Central Government University Foundation under grant JB2016045.

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Authors and Affiliations

  1. School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China

    Peixiu An & Zhitao Guan

Authors
  1. Peixiu An
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  2. Zhitao Guan
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Corresponding author

Correspondence to Zhitao Guan .

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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An, P., Guan, Z. (2016). Efficient Detection Method for Data Integrity Attacks in Smart Grid. 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_21

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  • DOI: https://doi.org/10.1007/978-3-319-49148-6_21

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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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