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False Data Injection Attacks in Internet of Things

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Performability in Internet of Things

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

Internet of Things (IoT) facilitates networking among different types of electronic devices. The emerging false data injection attacks (FDIAs) have drawn attention and heavily researched in power systems and smart grid. The cyber criminals compromise a networked device and inject data. However, these attacks on IoT may lead to significant losses and able to disrupt normal activities among the devices in any IoT network. To the best of our knowledge, there is not enough substantial investigation on FDIA in IoT. Therefore, in this chapter, the impact of FDIA is analyzed from IoT perspective and the usefulness of existing FDIA countermeasures is investigated. The key contribution of this chapter is to create a new direction of IoT research on FDIA detection and prevention. The chapter will be beneficial for graduate level students, academicians, and researchers in this application domain.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Bangladesh

    Biozid Bostami

  2. Centre for Cyber Security and Games, Canberra Institute of Technology, REID, Australian Capital Territory, Australia

    Mohiuddin Ahmed

  3. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Salimur Choudhury

Authors
  1. Biozid Bostami
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  2. Mohiuddin Ahmed
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  3. Salimur Choudhury
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Corresponding author

Correspondence to Mohiuddin Ahmed .

Editor information

Editors and Affiliations

  1. Computer Engineering Department, Antalya Bilim University, Antalya, Turkey

    Fadi Al-Turjman

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Bostami, B., Ahmed, M., Choudhury, S. (2019). False Data Injection Attacks in Internet of Things. In: Al-Turjman, F. (eds) Performability in Internet of Things. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-93557-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-93557-7_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93556-0

  • Online ISBN: 978-3-319-93557-7

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