Detail publikace

A Survey on the Use of Deep Learning Techniques for UAV Jamming and Deception

ŠIMON, O. GÖTTHANS, T.

Originální název

A Survey on the Use of Deep Learning Techniques for UAV Jamming and Deception

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Unmanned aerial vehicles (UAVs) can be used for a variety of illegal activities (e.g., industrial espionage, smuggling, terrorism). Given their growing popularity and availability, and advances in communications technology, more sophisticated ways to disable these vehicles must be sought. Various forms of jamming are used to disable drones, but more advanced techniques such as deception and UAV takeover are considerably difficult to implement, and there is a large research gap in this area., Currently, machine and deep learning techniques are popular and are also used in various drone-related applications. HOwever, no detailed research has been conducted so far on the use of these techniques for jamming and deception of UAVs. This paper focuses on exploring the current techniques in the are of jamming and deception. A survey on the use of machine or deep learning specifically in UAV-related applicsations is also conducted. The paper provides insight into the issues described and encourages more detailed research in this area.

Klíčová slova

UAV, jamming, machine learning, deep learning

Autoři

ŠIMON, O.; GÖTTHANS, T.

Vydáno

23. 9. 2022

Nakladatel

MDPI

ISSN

2079-9292

Periodikum

Electronics (MDPI)

Ročník

11

Číslo

19

Stát

Švýcarská konfederace

Strany od

1

Strany do

32

Strany počet

32

URL

https://www.mdpi.com/2079-9292/11/19/3025

Plný text v Digitální knihovně

http://hdl.handle.net/11012/208687

BibTex

@article{BUT179296,
  author="Ondřej {Šimon} and Tomáš {Götthans}",
  title="A Survey on the Use of Deep Learning Techniques for UAV Jamming and Deception",
  journal="Electronics (MDPI)",
  year="2022",
  volume="11",
  number="19",
  pages="1--32",
  doi="10.3390/electronics11193025",
  issn="2079-9292",
  url="https://www.mdpi.com/2079-9292/11/19/3025"
}