Publication detail

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

ŠIMON, O. GÖTTHANS, T.

Original Title

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

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

UAV, jamming, machine learning, deep learning

Authors

ŠIMON, O.; GÖTTHANS, T.

Released

23. 9. 2022

Publisher

MDPI

ISBN

2079-9292

Periodical

Electronics (MDPI)

Year of study

11

Number

19

State

Swiss Confederation

Pages from

1

Pages to

32

Pages count

32

URL

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

Full text in the Digital Library

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"
}