Wireless attacks against commercial drones: a systematic mapping study

Authors

  • Brayan Pajuelo-Martin Universidad de Buenos Aires. Viamonte 430, Ciudad Autónoma de Buenos Aires, Argentina https://orcid.org/0009-0007-5945-4006
    Competing Interests

    No conflict of interest

  • William-Rogelio Marchand-Niño Universidad Nacional Agraria de la Selva. Carretera Central km. 1.21; Tingo María, Huánuco, Perú https://orcid.org/0000-0003-2650-4226
    Competing Interests

    none

DOI:

https://doi.org/10.37636/recit.v9n2e444

Keywords:

Wireless attacks, Drones, Vulnerabilities, Mitigation, Cybersecurity, Systematic mapping

Abstract

This study compiles wireless cyberattacks carried out experimentally against drones. It focuses on three areas of analysis: first, the types of attacks; second, their vulnerabilities; and finally, the proposed mitigation measures. The scope is limited to studies conducted between 2020 and 2024. Following the methodology, a search query was applied to the Scopus and IEEE Xplore databases. An initial search yielded 6,860 articles, and after applying our inclusion and exclusion criteria, 28 articles were selected, which guided the entire analysis of this research. The most common attacks found were spoofing and jamming. These attacks exploit the reliance on the Global Navigation Satellite System (GNSS) and the lack of a robust authentication system. Among the vulnerabilities identified are the absence of an intrusion detection system (IDS) as well as weaknesses in encryption. The literature proposed mitigation measures such as the use of anti-interference techniques (DSSS and FHSS), cross-validation of signals, IDS, and strong authentication. It was concluded that strict regulatory policies are needed to improve cybersecurity in drones. These types of attacks must also be validated on high-end drones.

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References

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Diagram of the document selection process.

Published

2026-06-13

How to Cite

Pajuelo-Martin, B., & Marchand-Niño, W.-R. (2026). Wireless attacks against commercial drones: a systematic mapping study. Revista De Ciencias Tecnológicas, 9(2), 1-16. https://doi.org/10.37636/recit.v9n2e444

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