A Comprehensive Survey on RIS-Enhanced Physical Layer Security in UAV-Assisted Networks

This survey provides an in-depth examination of the role of reconfigurable intelligent surfaces (RIS) in enhancing physical layer security (PLS) within unmanned aerial vehicle (UAV)-assisted networks, which are essential for the secure and efficient operation of sixth-generation (6G) wireless communications. The study covers various types of RIS—passive, active, and hybrid—and their applications in both terrestrial and aerial environments to strengthen PLS. Key focus areas include advanced PLS techniques such as optimizing UAV trajectory, beamforming, and RIS phase-shift configurations, all aimed at improving secrecy rates (SRs) while mitigating the risks of eavesdropping and jamming. Moreover, the survey also addresses strategies for enhancing energy-efficient SRs and implementing anti-jamming mechanisms within UAV-assisted networks. Additionally, it explores the integration of RIS-UAV systems with emerging technologies such as non-orthogonal multiple access (NOMA), mobile edge computing (MEC), cognitive radio, and THz networks, demonstrating how security can be enhanced in such networks. Through detailed performance analysis, the paper highlights the transformative potential of RIS-equipped UAVs in overcoming the potential security challenges for future 6G networks. Finally, the survey presents lessons learned and identifies critical future research directions and open challenges, offering insights that will guide the development of robust and secure RIS-assisted UAV systems in next-generation wireless networks.

Authors

Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-16
DOI
https://doi.org/10.1109/jiot.2025.3569716
Citations
19
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
94.88
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comprehensive Survey on RIS-Enhanced Physical Layer Security in UAV-Assisted Networks

Yongxiao Li, Aized Amin Soofi, Manzoor Ahmed, Feroz Khan et al.
19 citations
IEEE Internet of Things Journal
UAV Applications and Optimization
94.88
article

A Comprehensive Survey on RIS-Enhanced Physical Layer Security in UAV-Assisted Networks

Yongxiao Li, Aized Amin Soofi, Manzoor Ahmed, Feroz Khan, Zhu Han, Muhammad Asif, Salman Raza, Wali Ullah Khan
article en
19 citations

Abstract

This survey provides an in-depth examination of the role of reconfigurable intelligent surfaces (RIS) in enhancing physical layer security (PLS) within unmanned aerial vehicle (UAV)-assisted networks, which are essential for the secure and efficient operation of sixth-generation (6G) wireless communications. The study covers various types of RIS—passive, active, and hybrid—and their applications in both terrestrial and aerial environments to strengthen PLS. Key focus areas include advanced PLS techniques such as optimizing UAV trajectory, beamforming, and RIS phase-shift configurations, all aimed at improving secrecy rates (SRs) while mitigating the risks of eavesdropping and jamming. Moreover, the survey also addresses strategies for enhancing energy-efficient SRs and implementing anti-jamming mechanisms within UAV-assisted networks. Additionally, it explores the integration of RIS-UAV systems with emerging technologies such as non-orthogonal multiple access (NOMA), mobile edge computing (MEC), cognitive radio, and THz networks, demonstrating how security can be enhanced in such networks. Through detailed performance analysis, the paper highlights the transformative potential of RIS-equipped UAVs in overcoming the potential security challenges for future 6G networks. Finally, the survey presents lessons learned and identifies critical future research directions and open challenges, offering insights that will guide the development of robust and secure RIS-assisted UAV systems in next-generation wireless networks.

IEEE Internet of Things JournalVol. 12(16)
Jiangsu University (CN), Gachon University (KR), Beijing University of Posts and Telecommunications (CN), National University of Modern Languages (PK), Academic Degrees & Graduate Education (CN), Hubei Engineering University (CN), University of Houston (US), National Textile University (PK)
Affordable and clean energy
Openalex Percentile: Top 0%
UAV Applications and Optimization
94.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.