Evidence map›Paper›PMID 41507349›Full record

ArticleScientific reports2026

Covert underwater communication through cepstrum modulation mimicking Pseudorca crassidens whistles using machine learning.

Muhammad Bilal, Habib Hussain Zuberi, Amar Jaffar, Waqar Riaz, Mohsin Abrar Khan, Ayman Alharbi, Abdulaziz Miyajan, Songzuo Liu

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Muhammad BilalSchool of Engineering, Nanfang College Guangzhou, Guangzhou, 510970, China. bilalmuhammad@nfu.edu.cn.
Habib Hussain ZuberiElectrical Engineering department, Bahria University, Karachi campus, Karachi, 73500, Pakistan.
Amar JaffarComputer and Network Engineering Department, College of Computing, Umm Al-Qura University, Mecca, 24231, Saudi Arabia.
Waqar RiazSchool of Engineering, Nanfang College Guangzhou, Guangzhou, 510970, China. riazwaqar@nfu.edu.cn.
Mohsin Abrar KhanCollege of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, 150001, China.
Ayman AlharbiComputer and Network Engineering Department, College of Computing, Umm Al-Qura University, Mecca, 24231, Saudi Arabia.
Abdulaziz MiyajanComputer and Network Engineering Department, College of Computing, Umm Al-Qura University, Mecca, 24231, Saudi Arabia.
Songzuo LiuCollege of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, 150001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing demand for clandestine communication in underwater acoustic environment reflects the remarkable growth of research in underwater acoustic communication and networking. Mariners are driven to transmit information covertly in the ocean keeping it hidden from unfriendly users and intruders. This research introduces a novel technique of covert underwater acoustic communication that mimics false killer whale whistles. The secret information is embedded using cepstrum transform to imitate Pseudorca crassidens whistles. This covert communication can be achieved even in the presence of eavesdroppers, who are unable to recognize the communication signal due to unique watermarking characteristics. The proposed model uses machine learning to assess imperceptibility and demonstrates exceptional robustness and improved capacity. To validate the model for secure communication and networks, underwater experiments were conducted, resulting in superior bit error rate and high watermark capacity with a perfect low probability of recognition constraint covert communication.

Indexed as

AcousticsMachine LearningVocalization, AnimalAnimalsBionicCepstrumClandestine communicationCovert underwater communicationFalse killer whale whistlesLow probability of recognitionMimicryPseudorca crassidens

Identifiers

PMID41507349
PMCPMC12858932

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.