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Unmanned Aerial Vehicles (UAVs) Threat Analysis and a Routine Activity Theory Based Mitigation Approach

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National Cyber Summit (NCS) Research Track (NCS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1055))

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Abstract

With the evolution of technology in today’s modern society comes the global success of unmanned aerial vehicles (UAVs; also known as drones). There are, however, opportunities for UAVs to be abused in criminal or nefarious activities. The aim of this paper is to outline the opportunities for UAVs to be used in criminal activities, and explore the potential countermeasures and their effectiveness. This paper will seek to apply Routine Activity Theory to reduce the opportunities for UAV related crime and theorise strategies to increase accountability. Finally, this paper will attempt to forecast the threat of a criminal act within 2019.

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Acknowledgements

The assistance of Michaela Bradshaw in preparing this paper is acknowledged.

Author information

Authors and Affiliations

  1. Digital Forensics Unit, West Midlands Police, West Midlands, UK

    Alan Roder

  2. Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Kim-Kwang Raymond Choo

Authors
  1. Alan Roder
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  2. Kim-Kwang Raymond Choo
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Corresponding author

Correspondence to Alan Roder .

Editor information

Editors and Affiliations

  1. The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  2. University of Alabama in Huntsville, Huntsville, AL, USA

    Thomas H. Morris

  3. Air Force Institute of Technology, Wright-Patterson AFB, OH, USA

    Gilbert L. Peterson

Appendix A: Crime Type Severity Guide

Appendix A: Crime Type Severity Guide

figure a

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Roder, A., Choo, KK.R. (2020). Unmanned Aerial Vehicles (UAVs) Threat Analysis and a Routine Activity Theory Based Mitigation Approach. In: Choo, KK., Morris, T., Peterson, G. (eds) National Cyber Summit (NCS) Research Track. NCS 2019. Advances in Intelligent Systems and Computing, vol 1055. Springer, Cham. https://doi.org/10.1007/978-3-030-31239-8_9

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