Cited by 12Underwater Vehicles and Communication SystemsUnderwater Acoustics ResearchMarine animal studies overview

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Acoustic projectors make covert bioacoustic chirplet signals discoverable

Open access
Casari, Paolo, Neasham, Jeff, Gubnitsky, Guy, Eccher, Davide, Diamant, Roee·2023·Scientific Reports

Abstract

To disguise man-made communications as natural signals, underwater transceivers have the option to pre-record animal vocalizations, and play them back in a way that carries meaningful information for a trained receiver. This operation, known as biomimicking, has been used to perform covert communications and to emit broadband signals for localization, either by playing pre-recorded animal sounds back into the environment, or by designing artificial waveforms whose spectrum is close to that of bioacoustic sounds.However, organic sound-emitting body structures in animals have very different trans-characteristics with respect to electro-acoustic transducers used in underwater acoustic transceivers. In this paper, we observe the distortion induced by transmitting pre-recorded animal vocalization through a transducer’s front-end, and argue that such distortion can be detected via appropriate entropy metrics. We test ten different metrics for this purpose, both via emulated transmission and in two field experiments. Our result indicate which signals and entropy metrics lead to the highest probability of detecting transducer-originated distortions, thus exposing ongoing covert communications. Our research emphasizes the limitations that man-made equipment incurs when reproducing bioacoustic sounds, and prompts for the choice of biomimicking signals that are possibly suboptimal for communications or localization, but help avoid exposing disguised transmissions.

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Research works printed but not linked: 2

  1. Dol, H., Quesson, B. & Benders, F. Covert underwater communication with marine mammal sounds. In Proceeding of UDT (2008).
  2. Hu, X., Jiang, J., Cao, D. & Egardt, B. Battery health prognosis for electric vehicles using sample entropy and sparse Bayesian predictive modeling. IEEE Trans. Ind. Electron. 63, 2645–2656 (2015).

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Metadata

Authors
Casari, P., Neasham, J., Gubnitsky, G., Eccher, D., & Diamant, R.
Affiliations
  • University of Trento (IT)
  • University of Haifa (IL)
Corresponding author
Casari, Paolo
Venue
Scientific Reports
Published
2023-02-14
Volume
13
Issue
1
Pages
2591-2591
ISSN
2045-2322 (ISSN-L)
OpenAlex
W4320727230
Cited by
12
References
27
Citations by year
2026: 4 · 2025: 3 · 2024: 3 · 2023: 2
FWCI
1.46
Type
journal article
Language
en
Open access
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Iris (University of Trento) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Newcastle University ePrints (Newcastle Univesity) (cc-by)
Funders
  • NATO Science for Peace and Security (G5884)
  • Ministero dell’Economia e delle Finanze,Italy (ECS 00000043)
Topics
  • Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Underwater Acoustics Research
  • Physical Sciences › Environmental Science › Ecology › Marine animal studies overview
Keywords
entropy measures, sound localization
MeSH terms
Acoustics, Animals, Communication, Sound, Vocalization, Animal

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