Game of Drones - Detecting Spying Drones Using Time Domain Analysis

Ben Nassi, Raz Ben-Netanel, Adi Shamir, Yuval Elovici

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

1 Scopus citations


Drones have created a new threat to people’s privacy. We are now in an era in which anyone with a drone equipped with a video camera can use it to invade a subject privacy by filming the subject in his/her private space using encrypted First Person View (FPV) channel. Although many methods have been suggested to detect a nearby drone, they all suffer from the same shortcoming: they cannot detect what specifically is being captured and therefore they fail to distinguish between the legitimate use of a drone that does not invade a subject’s privacy (for example, neighbor’s drone flying and shoot his garden) and illegitimate use (same drone shooting the subject’s property), where in many cases depends on the orientation of the drone’s video camera rather than on the drone’s location. In this paper we present a method that utilizes a flicker in order to detect whether the drone’s camera is directed towards the private space by analyzing the encrypted video stream sent from the drone in real time. We investigate the influence of changing pixels on the transmitted traffic (in a lab setup). We leverage our conclusions and demonstrate how an interceptor can apply a side-channel attack to detect that a subject is video streamed by DJI Mavic drone from its encrypted FPV channel when the subject is located inside a private house.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - 5th International Symposium, CSCML 2021, Proceedings
EditorsShlomi Dolev, Oded Margalit, Benny Pinkas, Alexander Schwarzmann
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages17
ISBN (Print)9783030780852
StatePublished - 1 Jan 2021
Event5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021 - Be'er Sheva, Israel
Duration: 8 Jul 20219 Jul 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12716 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021
CityBe'er Sheva


  • Cryptanalysis
  • Drones
  • Side channels

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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