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Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities

Journal Article · · Security Journal
 [1];  [2];  [3];  [4]
  1. Khalifa Univ., Abu Dhabi (United Arab Emirates); Gulf Nuclear Energy Infrastructure Institute (GNEII), Abu Dhabi (United Arab Emirates)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Khalifa Univ., Abu Dhabi (United Arab Emirates)
  4. Virginia Commonwealth Univ., Richmond, VA (United States)

Unmanned aerial vehicles (UAV) are among the major growing technologies that have many beneficial applications, yet they can also pose a significant threat. Recently, several incidents occurred with UAVs violating privacy of the public and security of sensitive facilities, including several nuclear power plants in France. The threat of UAVs to the security of nuclear facilities is of great importance and is the focus of this work. This paper presents an overview of UAV technology and classification, as well as its applications and potential threats. We show several examples of recent security incidents involving UAVs in France, USA, and United Arab Emirates. Further, the potential threats to nuclear facilities and measures to prevent them are evaluated. The importance of measures for detection, delay, and response (neutralization) of UAVs at nuclear facilities are discussed. An overview of existing technologies along with their strength and weaknesses are shown. Finally, the results of a gap analysis in existing approaches and technologies is presented in the form of potential technological and procedural areas for research and development. Furthermore based on this analysis, directions for future work in the field can be devised and prioritized.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1356834
Report Number(s):
SAND2017-3408J; 652157
Journal Information:
Security Journal, Journal Name: Security Journal Journal Issue: 1 Vol. 31; ISSN 0955-1662
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (2)

V-RBNN Based Small Drone Detection in Augmented Datasets for 3D LADAR System journal November 2018
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks journal August 2019

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