MAG-JAM: Jamming Detection via Magnetic Emissions

Omar Adel Ibrahim*, Roberto Di Pietro

*Corresponding author for this work

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

Abstract

Wireless networks inherently rely on a shared medium, making them exposed to jamming attacks. In this paper, we present MAG-JAM, a novel solution for jamming detection in static and mobile scenarios leveraging the physical layer properties of wireless communication by analyzing the magnetic emissions near the antennas of target wireless devices. To the best of our knowledge, MAG-JAM represents the first solution based on the key observation that the magnetic emissions profile of normal wireless communication between transmitter-receiver pairs is different from the magnetic emissions profile when an active jamming signal starts affecting the communication channel. MAG-JAM has several advantages: its implementation requires mainly an inexpensive magnetic sensor, it is non-invasive and privacy-preserving as it is implemented as a standalone unit, does not need access to the wireless device, and demonstrates a remarkable performance. We design and implement a proof of concept jamming detection system using a cheap magnetic sensor and test MAG-JAM on a set of different wireless devices with a perfect score in jamming detection using no more than 1 s of the magnetic emissions collected by the magnetic sensor under a normalized jamming power of 0.1–1. In addition, we also implement a more advanced jamming detection system using a specialized magnetic probe and autoencoders that, using just 150 ms of collected data, achieves a minimum of 0.91 F1-Score in detecting jamming with a normalized power of 0.2 and an F1-Score of 1 for jamming powers greater than 0.4.

Original languageEnglish (US)
Title of host publicationComputer Security – ESORICS 2024 - 29th European Symposium on Research in Computer Security, Proceedings
EditorsJoaquin Garcia-Alfaro, Rafał Kozik, Michał Choraś, Sokratis Katsikas
PublisherSpringer Science and Business Media Deutschland GmbH
Pages167-186
Number of pages20
ISBN (Print)9783031708787
DOIs
StatePublished - 2024
Event29th European Symposium on Research in Computer Security, ESORICS 2024 - Bydgoszcz, Poland
Duration: Sep 16 2024Sep 20 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14982 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference29th European Symposium on Research in Computer Security, ESORICS 2024
Country/TerritoryPoland
CityBydgoszcz
Period09/16/2409/20/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • Deep Learning
  • Jamming Detection
  • Magnetic Emissions
  • Physical Layer
  • Wireless Security

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'MAG-JAM: Jamming Detection via Magnetic Emissions'. Together they form a unique fingerprint.

Cite this