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Spoof Detection in a Zigbee Network Using Forge-Resistant Network Characteristics (RSSI and LQI)

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Information and Communication Technology and Applications (ICTA 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1350))

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Abstract

The development of a spoof detection framework in a ZigBee network using forge-resistant network characteristics is presented. ZigBee has become ubiquitous in application areas such as Wireless Sensor Networks (WSNs), Home Area Networks (HANs), Smart Metering, Smart Grid, Internet of Things (IoT) and smart devices. Its pervasiveness and suitability for vast applications makes it a tempting target for attackers. Due to the open nature of the wireless medium, ZigBee networks are susceptible to spoofing attacks; where an illegitimate/Sybil node impersonates or disguises as one or multiple legitimate nodes with malicious intentions. A testbed consisting of two ZU10 ZigBee modules was setup to create a real ZigBee network environment. Received Signal Strength Indicator (RSSI) and the corresponding Link Quality Indicator (LQI) data were collected. The Dynamic Time Warping (DTW) algorithm was used for time series classification and similarity measurement of these dataset over variable physical distances. The framework was able to differentiate ZigBee signals that are at least 1 m apart.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, Ahmadu Bello University, Samaru, Zaria, Kaduna, Nigeria

    Christopher Bahago Martins, Emmanuel Adedokun Adewale, Ime Umoh Jarlath & Muhammed Bashir Mu’azu

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  1. Christopher Bahago Martins
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  2. Emmanuel Adedokun Adewale
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  3. Ime Umoh Jarlath
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  4. Muhammed Bashir Mu’azu
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Corresponding author

Correspondence to Christopher Bahago Martins .

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Editors and Affiliations

  1. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. Federal University of Technology Minna, Minna, Nigeria

    Bilkisu Muhammad-Bello

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Martins, C.B., Adewale, E.A., Jarlath, I.U., Mu’azu, M.B. (2021). Spoof Detection in a Zigbee Network Using Forge-Resistant Network Characteristics (RSSI and LQI). In: Misra, S., Muhammad-Bello, B. (eds) Information and Communication Technology and Applications. ICTA 2020. Communications in Computer and Information Science, vol 1350. Springer, Cham. https://doi.org/10.1007/978-3-030-69143-1_26

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  • DOI: https://doi.org/10.1007/978-3-030-69143-1_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69142-4

  • Online ISBN: 978-3-030-69143-1

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