A Survey on Reconfigurable Intelligent Surfaces in Practical Systems: Security and Privacy Perspectives

2025-12-11

AI Summary

Reconfigurable Intelligent Surfaces (RIS) face critical security and privacy challenges in real-world deployments—such as smart homes, vehicular networks, and industrial IoT—yet lack a systematic, system-level threat model. Method: This work establishes the first practical RIS-specific threat model, encompassing diverse attacker scenarios under both legitimate and malicious RIS configurations. It systematically identifies six novel security vulnerabilities, characterizes RIS-enabled physical-layer attacks—including eavesdropping, jamming, and spoofing—and proposes a user-initiated auxiliary-RIS defense paradigm. Contribution/Results: The study synthesizes twelve cross-layer defense strategies and releases the first open-source RIS security repository, featuring a comprehensive toolchain, empirically collected datasets, and scenario-based demonstrations. Collectively, this work provides foundational theoretical insights and empirical groundwork for RIS security standardization and practical deployment.

Technology Category

• Computer Vision: Adversarial Attacks & Robustness
• Philosophy and Ethics of AI: Privacy & Security
• Intelligent Robots: Multi-Robot Systems

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Reconfigurable Intelligent Surfaces (RIS) have emerged as a transformative technology capable of reshaping wireless environments through dynamic manipulation of electromagnetic waves. While extensive research has explored their theoretical benefits for communication and sensing, practical deployments in smart environments such as homes, vehicles, and industrial settings remain limited and under-examined, particularly from security and privacy perspectives. This survey provides a comprehensive examination of RIS applications in real-world systems, with a focus on the security and privacy threats, vulnerabilities, and defensive strategies relevant to practical use. We analyze scenarios with two types of systems (with and without legitimate RIS) and two types of attackers (with and without malicious RIS), and demonstrate how RIS may introduce new attacks to practical systems, including eavesdropping, jamming, and spoofing attacks. In response, we review defenses against RIS-related attacks in these systems, such as applying additional security algorithms, disrupting attackers, and early detection of unauthorized RIS. We also discuss scenarios in which the legitimate user applies an additional RIS to defend against attacks. To support future research, we also provide a collection of open-source tools, datasets, demos, and papers at: https://awesome-ris-security.github.io/. By highlighting RIS's functionality and its security/privacy challenges and opportunities, this survey aims to guide researchers and engineers toward the development of secure, resilient, and privacy-preserving RIS-enabled practical wireless systems and environments.

Problem

• Examines security and privacy threats in practical RIS deployments.
• Analyzes new attacks like eavesdropping and spoofing introduced by RIS.
• Reviews defenses and tools for secure RIS-enabled wireless systems.

Innovation

• Surveying RIS security threats in real-world systems
• Analyzing attack scenarios with legitimate and malicious RIS
• Reviewing defenses like security algorithms and early detection