RIS-Based Physical Layer Security for Integrated Sensing and Communication: A Comprehensive Survey

Integrated Sensing and Communication (ISAC) is a crucial component of future wireless networks, enabling seamless integration of Communication and Sensing (C&S) functionalities. However, ensuring security in ISAC systems remains a significant challenge, as both C&S data are susceptible to adversarial threats. Physical Layer Security (PLS) has emerged as a key framework for mitigating these risks at the transmission level. Reconfigurable Intelligent Surfaces (RIS) further enhance PLS by dynamically shaping the radio environment to improve both secrecy along with C&S performance. This survey begins with an overview of RIS, PLS, and ISAC fundamentals, establishing a foundation for understanding their integration. The state-of-the-art RIS-assisted PLS approaches in ISAC systems are then categorized into Passive RIS (PRIS) and Active RIS (ARIS) paradigms. PRIS-based techniques focus on optimizing system throughput, covert communication, and Secrecy Rates (SRs), alongside improving sensing Signal-to-Noise Ratio (SNR) and Weighted Sum Rate (WSR) under various constraints. ARIS-based strategies extend these capabilities by actively optimizing beamforming to enhance secrecy and covert rates while ensuring robust sensing under communication and security constraints. By reviewing both passive and ARIS-based security frameworks, this survey highlights the transformative role of RIS in strengthening ISAC security. Furthermore, it explores key optimization methodologies, technical challenges, and future research directions for integrating RIS with PLS to ensure secure and efficient ISAC in next-generation 6G wireless networks.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-06
DOI
https://doi.org/10.1109/jiot.2025.3567553
Citations
23
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
15.50
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article

RIS-Based Physical Layer Security for Integrated Sensing and Communication: A Comprehensive Survey

Chandan Kumar Sheemar, Aized Amin Soofi, Manzoor Ahmed, Zhu Han et al.
23 citations
IEEE Internet of Things Journal
Wireless Body Area Networks
15.50
article

RIS-Based Physical Layer Security for Integrated Sensing and Communication: A Comprehensive Survey

Chandan Kumar Sheemar, Aized Amin Soofi, Manzoor Ahmed, Zhu Han, Yongxiao Li, Muhammad Asif, Feroz Khan, Wali Ullah Khan
article en
23 citations

Abstract

Integrated Sensing and Communication (ISAC) is a crucial component of future wireless networks, enabling seamless integration of Communication and Sensing (C&S) functionalities. However, ensuring security in ISAC systems remains a significant challenge, as both C&S data are susceptible to adversarial threats. Physical Layer Security (PLS) has emerged as a key framework for mitigating these risks at the transmission level. Reconfigurable Intelligent Surfaces (RIS) further enhance PLS by dynamically shaping the radio environment to improve both secrecy along with C&S performance. This survey begins with an overview of RIS, PLS, and ISAC fundamentals, establishing a foundation for understanding their integration. The state-of-the-art RIS-assisted PLS approaches in ISAC systems are then categorized into Passive RIS (PRIS) and Active RIS (ARIS) paradigms. PRIS-based techniques focus on optimizing system throughput, covert communication, and Secrecy Rates (SRs), alongside improving sensing Signal-to-Noise Ratio (SNR) and Weighted Sum Rate (WSR) under various constraints. ARIS-based strategies extend these capabilities by actively optimizing beamforming to enhance secrecy and covert rates while ensuring robust sensing under communication and security constraints. By reviewing both passive and ARIS-based security frameworks, this survey highlights the transformative role of RIS in strengthening ISAC security. Furthermore, it explores key optimization methodologies, technical challenges, and future research directions for integrating RIS with PLS to ensure secure and efficient ISAC in next-generation 6G 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), University of Luxembourg (LU), Hubei Engineering University (CN), University of Houston (US)
Openalex Percentile: Top 1%
Wireless Body Area Networks
15.50
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