Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities
- Khalifa Univ., Abu Dhabi (United Arab Emirates); Gulf Nuclear Energy Infrastructure Institute (GNEII), Abu Dhabi (United Arab Emirates)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Khalifa Univ., Abu Dhabi (United Arab Emirates)
- 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
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 |
Similar Records
Unmanned Aerial Vehicle (UAV) Dynamic-Tracking Directional Wireless Antennas for Low Powered Applications that Require Reliable Extended Range Operations in Time Critical Scenarios
Synthesis of the unmanned aerial vehicle remote control augmentation system