Evidence map›Paper›PMID 41600430›Full record

ReviewSensors (Basel, Switzerland)2026

Security of ADS-B and Remote ID Systems: Cyberattacks, Detection Techniques, and Countermeasures.

Qinxuan Shi, Toro Dama Caleb, Sicong Shao, Naima Kaabouch

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Qinxuan ShiSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.ORCID 0009-0003-9062-1782
Toro Dama CalebSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.ORCID 0000-0002-5147-9942
Sicong ShaoSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.ORCID 0000-0003-1205-3890
Naima KaabouchSchool of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aviation sector relies on cooperative surveillance systems such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Remote Identification (RID) to enhance safety and efficiency. However, their open, unencrypted communication protocols make them vulnerable to various cyberattacks. This survey examines the current state of knowledge on attacks, detection techniques, and countermeasures for both ADS-B and RID, addressing a gap in the literature by analyzing them side by side. It categorizes attacks, including emerging threats, reviews detection methods from traditional to modern AI-based approaches and discusses existing countermeasures. Furthermore, this paper provides a list of simulation tools and open-access datasets and identifies current research challenges and future directions.

Indexed as

ADS-Battack countermeasuresattack detectioncybersecurityRemote IDrisk analysisunmanned aerial system

Identifiers

PMID41600430
PMCPMC12846276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.