Can the Operator of a Drone Be Located by Following the Drone’s Path?

Eliyahu Mashhadi, Yossi Oren, Gera Weiss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Small commercial Unmanned Aerial Systems (UASs), called drones in common language, pose significant security risks due to their agility, high availability and low price. There is, therefor, a growing need to develop methods for detection, localization and mitigation of malicious and other harmful operation of these drones. This paper presents our work towards autonomously localizing drone operators based only on following their path in the sky. We use a realistic simulation environment and collect the path of the drone when flown from different points of view. A deep neural network was trained to be able to predict the location of drone operators, given the path of the drones. The model is able to achieve prediction of the location of the location of the operator with 73% accuracy.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - 4th International Symposium, CSCML 2020, Proceedings
EditorsShlomi Dolev, Gera Weiss, Vladimir Kolesnikov, Sachin Lodha
PublisherSpringer
Pages85-93
Number of pages9
ISBN (Print)9783030497842
DOIs
StatePublished - 1 Jan 2020
Event4th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020 - Beersheba, Israel
Duration: 2 Jul 20203 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12161 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020
Country/TerritoryIsrael
CityBeersheba
Period2/07/203/07/20

Keywords

  • Deep learning
  • Deep neural network
  • Drone
  • Security
  • Surveillance
  • UAS

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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