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Faulty or Malicious Anchor Detection Criteria for Distance-Based Localization

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Critical Information Infrastructures Security (CRITIS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10707))

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Abstract

The reliability of the localization of Wireless Sensor Networks in presence of errors or malicious data alteration is a challenging research topic: recently, several studies have been carried out to identify, remove or neglect the faulted/malicious nodes. This paper addresses the capability of a network, composed of range-capable nodes and anchor nodes (i.e., nodes that know their position), to detect a faulty or malicious alteration of the information provided by the anchor nodes. Specifically, we consider biases for the position of anchor nodes that alter the localization of the network, and we provide conditions under which the nodes are able to detect the event, with particular reference to two distance-based localization algorithms, namely trilateration and Shadow Edge Localization Algorithm.

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Author information

Authors and Affiliations

  1. Department of Engineering, University Rome Tre, Via della Vasca Navale 79, 00146, Rome, Italy

    Federica Inderst, Stefano Panzieri & Federica Pascucci

  2. Complex Systems and Security Laboratory, University Campus Bio-Medico of Rome, Via A. del Portillo 21, 00128, Rome, Italy

    Gabriele Oliva & Roberto Setola

Authors
  1. Federica Inderst
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  2. Gabriele Oliva
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  3. Stefano Panzieri
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  4. Federica Pascucci
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  5. Roberto Setola
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Corresponding author

Correspondence to Federica Pascucci .

Editor information

Editors and Affiliations

  1. ENEA “Casaccia” and Network of Networks - Netonets, Rome, Italy

    Gregorio D'Agostino

  2. CNR - Institute for Complex Systems (ISC), Rome, Italy

    Antonio Scala

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Inderst, F., Oliva, G., Panzieri, S., Pascucci, F., Setola, R. (2018). Faulty or Malicious Anchor Detection Criteria for Distance-Based Localization. In: D'Agostino, G., Scala, A. (eds) Critical Information Infrastructures Security. CRITIS 2017. Lecture Notes in Computer Science(), vol 10707. Springer, Cham. https://doi.org/10.1007/978-3-319-99843-5_21

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  • DOI: https://doi.org/10.1007/978-3-319-99843-5_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99842-8

  • Online ISBN: 978-3-319-99843-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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