A joint optimization problem involving active and passive BF was formulated to maximize the SSR of trusted devices while ensuring performance guarantees for all trusted and untrusted devices. An algorithm based on the DDPG was introduced to obtain the optimal phases for RIS and the transmit BF matrix. The results demonstrated a significant increase in the SR of trusted devices. The authors of [109] introduced a DRL-based approach for a secure VLC system utilizing RIS. The adjustment of BF weights at light fixtures and mirror orientations within the mirror array sheet to optimize SR was controlled by the DDPG-based algorithm. The adaptability of the DDPG-based algorithm in managing the system's high complexity and user mobility was demonstrated. Findings indicated enhancing the security of the VLC communication system. In [196], the robust and secure transmission of RIS-assisted mmWave UAV communications was explored. A DDPG algorithm was introduced to maximize the SR for all authorized users. Simulation results confirmed that superior performance could be attained compared to several benchmark methods through the joint optimization of UAV trajectory and active (passive) BF.

2) *Deep Q-learning Algorithm:* deep Q-learning (DQN) extends the capabilities of the Q-learning algorithm by incorporating DNNs to manage intricate and high-dimensional state spaces effectively. In DQN, the conventional Q-table is replaced with a neural network called the Q-network, which approximates Q-values for each action within a given state. This adaptation equips DQN to navigate scenarios with continuous or extensive state spaces proficiently. The neural network undergoes training to minimize the disparity between its predicted and target Q-values, computed using the Bellman equation. DQN has demonstrated notable success in tackling demanding problems within RL, especially in domains like playing intricate video games, where the conventional Q-learning approach encounters challenges due to the expansive and continuous state space. Integrating DNNs enables DQN to generalize and acquire insights into intricate patterns, establishing it as a robust tool in AI.

Secure communications enabled by ARIS were explored in [205], employing ARIS deployment and passive BF, with the strategic design leveraging DQN. Simulation results revealed that the proposed DQN successfully approximated optimal deployment, resulting in significant improvements in security performance compared to baseline methods. Moreover, a better performance could be achieved with more reflecting elements. The authors of [213] presented ARIS, wherein UAV and RIS capabilities were utilized to enhance average downlink achievable rates in wireless networks. The implementation used Q-learning and DQN algorithms to evaluate the approach's effectiveness in enhancing security. The findings indicated that the DQN algorithm was more suitable than the Q-learning algorithm for systems with huge action and state spaces. In [328], the security of RIS-enabled wireless networks was investigated in the presence of intelligent attackers. The DQN was introduced to enable adaptive modulation of BS and RIS reflection BF. When an eavesdropping attempt was detected, the BS allocated a portion of transmit power to emit AN, disrupting eavesdroppers. The provided results demonstrated

the efficacy of the proposed strategy, contributing to enhancing the SR in RIS-assisted wireless communication systems.

## B. Unsupervised Learning

Unsupervised learning-based algorithms do not rely on labeled training data to enhance and optimize processes. Instead, these algorithms autonomously uncover patterns and structures within the data, making them particularly valuable in situations where labeled data is limited or costly to obtain. In [281], an ASR maximization for secure RIS-aided aeronautical Ad-hoc networks (AANET) has been designed through a deep unsupervised learning algorithm. Specifically, the proposed algorithm relied on a projection-based DNN to get suitable solutions. The DNN addresses the given optimization problem without constraints. Simultaneously, the projection method ensures that the DNN's output is subsequently mapped to the constrained domain.

## C. Lessons Learned

This subsection investigates the promising ML techniques for RIS-assisted PLS. Here are the key takeaways:

* Integrating ML techniques into RIS-assisted wireless communications to enhance PLS holds significant promise across various dimensions. Supervised and unsupervised ML algorithms offer robust frameworks for proactive threat detection and prevention, addressing attacks like eavesdropping, jamming attacks, and unauthorized access. Specifically, DDPG algorithms, known for managing continuous action spaces effectively, are pivotal in optimizing decision-making processes related to PLS. Supervised learning algorithms enable proactive threat detection by learning from labeled datasets to recognize security breach patterns, while DDPG's deterministic policy enhances decision precision in establishing secure communication channels and optimizing parameters like RIS phase shifts and beamforming matrices. Additionally, algorithms like DQN enhance security protocols in RIS-enabled systems by managing complex state spaces and optimizing deployment strategies to mitigate evolving security risks without relying on labeled data, making them cost-effective solutions for optimizing PLS in wireless networks.

* From Table VI, it is evident that much of the existing literature on RIS-enabled PLS in wireless networks assumes continuous phase shifts, implying infinite resolution, whereas practical implementations necessitate discrete phase shifts. This contrast highlights the gap between theoretical assumptions and real-world application scenarios. Furthermore, the majority of research efforts have focused on leveraging DRL to enhance secrecy performance in RIS-assisted PLS for wireless networks. However, there remains potential in exploring advanced ML techniques such as federated, graph-based, transfer, and quantum machine learning for optimizing RIS functionalities. Incorporating these advanced ML methods
offers novel insights and potentially superior performance in practical deployments, addressing existing constraints and paving the way for more robust and efficient RIS-assisted wireless communication systems.

# VIII. PERFORMANCE ANALYSIS FOR RIS-ASSISTED PLS

The performance analysis for RIS-assisted PLS represents an essential aspect of evaluating the potential of RIS technology in enhancing the security of wireless communication systems. In PLS, RIS holds promise for strengthening security measures by selectively adjusting signal characteristics, managing interference, and mitigating eavesdropping attempts. This section focuses on conducting a comprehensive performance analysis to assess the impact of RIS-assisted PLS in terms of SNR improvement, SC enhancement, and SOP reduction. By examining the performance of RIS-enabled systems under different scenarios, valuable insights can be gained into the significance and feasibility of leveraging RIS to enhance wireless communication systems' PLS.

## A. SNR Improvement with RIS

This subsection explores the SNR enhancement via RIS within the paradigm of PLS, highlighting its crucial role in mitigating noise and optimizing signal strength. Significantly, the adaptive nature of RIS facilitates dynamic adjustments, a feature of paramount significance in addressing varying interference patterns and ensuring high SNR. The high SNR extends to fortifying communication links, particularly in challenging urban settings. This increases communication reliability and directly impacts security by strengthening communication links against eavesdropping and other security threats. The secrecy capabilities of wireless communication systems enhanced by using the RIS were examined in the presence of a potential eavesdropper, where the RIS was strategically placed between the source and the intended user, creating an intelligent environment to maintain link security. The results confirmed the positive influence of RIS utilization on improving the secrecy performance of wireless systems [227], [350]. The performance analysis of secure communications assisted by RIS for discrete phase shifts was investigated in [342], [344], [351]. The security performance of a communication system aided by RIS was examined in [208], with spatially random UAVs serving as eavesdroppers. The obtained results highlighted the security enhancements achieved through the deployment of RIS. The secrecy performance of a relay communication system utilizing an RIS on a UAV was investigated in [352] in the presence of multiple ground eavesdroppers. Specifically, a UAV equipped with a RIS was a passive relay, forwarding signals from the BS to users. Secrecy performance for integrated satellite and UAV relay networks with multiple vehicle eavesdroppers was investigated in [258] by employing RIS. The UAV was used to relay the legitimate signal to the destination user, facilitated by RIS. The authors in [75], proposed a novel technique by designing active elements in RIS to overcome the double-fading problem introduced in the RIS-aided link in a wireless communications system to secure the transmission data. In this approach, the reflected

incident signal was amplified by RIS's active elements, departing from the sole reflective function observed in passive RIS modules. The analysis and simulation results revealed a significant reduction in the required size of the RIS to achieve a specified performance level when active elements were employed. Additionally, a practical design for active RIS was proposed.

## B. Secrecy Capacity Enhancement

This subsection focuses on enhancing SC through using RIS within the context of PLS. Recent research conveys how the reconfigurable nature of RIS strategically influences channel dynamics, strengthening the system's capacity for secure data transmission through adaptive configurations that dynamically manipulate signal propagation, offering insights into potential gains in secure communication. The results illustrate how the RIS contributes to heightened SC by dynamically adapting to the communication environment and strategically configuring itself to minimize the impact of potential eavesdropping attempts. Comparative analyses against scenarios without RIS intervention further highlight the high improvements in SC obtained by RIS. This integrated approach clarifies how RIS enhances SC, establishing its role as a promising technology in improving PLS. The effectiveness of STAR-RIS in enhancing security within the MISO network was explored in [353]. Three transmission protocols, energy splitting, mode selection, and time splitting, were examined to maximize the weighted sum secrecy rate. In [240], high passive BF gains for signal enhancement were achieved by RISs through the dynamic adjustment of their reflection coefficients, improving wireless security and RF-based wireless power transfer efficiency. A RIS-assisted secure SWIPT system was investigated for transferring information and power. The worst-case downlink secure communication scenario was addressed in [276], applying RIS-UAV as an aerial passive relay to enhance communication. The objective was to maximize the worst-case downlink secrecy rate by optimizing power allocation, RIS passive BF, and UAV trajectory. The results demonstrated the effectiveness of the proposed scheme compared to other benchmarks. The impact of hardware impairments on the secrecy performance of a mmWave system assisted by an RIS was investigated in [199]. In this regard, a system model was constructed without considering hardware impairments, and optimal solutions were presented for signal and AN powers, BF design, and phase shifts of the RIS elements. The authors in [354] explored the PLS of active RIS-assisted NOMA networks in the presence of external and internal eavesdroppers. Specifically, closed-form expressions for SOP and secrecy system throughput were derived, considering both imperfect SIC and perfect SIC. An innovative approach to enhancing the secrecy performance of a LPWAN by integrating an RIS with a UAV was introduced in [295]. The primary goal was to improve the secure data transmission between an IoT sensor and a gateway in LPWAN applications. Closed-form expressions for the SOP, PNSC, and ASR were derived for the proposed network operating over Nakagami-$m$ fading channels. Additionally, the practical impact of the
<table><caption>TABLE VII
SUMMARY OF PERFORMANCE ANALYSIS RELATED LITERATURE FOR RIS-ASSISTED PLS SYSTEMS</caption><thead><tr><th>[#]</th><th>Phase-shift resolution</th><th>Security attack</th><th>Eavesdropper type</th><th>Performance metric(s)</th><th>Main Findings</th></tr></thead><tbody><tr><td>[338]</td><td>Continuous</td><td>Jamming</td><td>Passive</td><td rowspan="10">SOP</td><td>Impacting of electromagnetic interference's on secrecy performance</td></tr><tr><td>[339]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Enhancing PLS using RIS</td></tr><tr><td>[115]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Analyzing secure RIS-assisted HAP-UAV joint MU mixed RF/FSO system</td></tr><tr><td>[340]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Utilizing cooperative jamming and BF design to improve PLS of NOMA</td></tr><tr><td>[341]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Utilizing cooperative jamming and BF design to improve PLS of NOMA</td></tr><tr><td>[342]</td><td>Discrete</td><td>Eavesdropping</td><td>Passive</td><td>Revealing the SOP's scaling law for RIS's elements and quantization's bits</td></tr><tr><td>[343]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Reducing the secrecy performance due to residual hardware impairments</td></tr><tr><td>[275]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Enhancing secrecy performance of V2V communications with the aid of RIS</td></tr><tr><td>[302]</td><td>Discrete</td><td>Eavesdropping</td><td>Passive</td><td>Investigating an RIS-aided ambient backscatter communication (BackCom) with perfect and imperfect CSI and showing the superior secrecy outage behaviours compared to the conventional BackCom networks</td></tr><tr><td>[227]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td rowspan="4">SOP, PNSC</td><td>Friendly Jamming Eve using RIS to improve the security performance</td></tr><tr><td>[229]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Improving the secrecy performance of primary network using secondary RIS</td></tr><tr><td>[239]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Designing phase shift to maximize information at the legitimate destination</td></tr><tr><td>[75]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Enhancing secrecy performance of wireless network using active RIS</td></tr><tr><td>[295]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td rowspan="2">SOP, PNSC, ASR</td><td>Improving a secure data transmission of LPWAN IoT sensor</td></tr><tr><td>[171]</td><td>Continuous</td><td>Jamming</td><td>Active</td><td>Reducing the secrecy performance due to residual hardware impairments</td></tr><tr><td>[344]</td><td>Discrete</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ASR</td><td>Unveiling the secrecy loss due to phase resolution</td></tr><tr><td>[345]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ASC</td><td>Investigating the effect of REs on the secrecy diversity orders</td></tr><tr><td>[174]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ESC</td><td>Showing the effects of RE on the SOP and ESC</td></tr><tr><td>[346]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ANT</td><td>HARQ is beneficial to improve system security-reliability balance</td></tr><tr><td>[188]</td><td>Continuous/ Discrete</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ESR</td><td>Investigating the fundamental limits of RIS-aided wiretap MIMO communications</td></tr><tr><td>[273]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SOP, IP</td><td>Showing that the active RIS improves the UAV system security and reliability tradeoff (SRT) more than passive and hybrid RIS</td></tr><tr><td>[116]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SOP, ASC, SPSC, EST</td><td>Exploring secure RIS-assisted relaying system for mixed RF/FSO system</td></tr><tr><td>[347]</td><td>Discrete</td><td>Eavesdropping</td><td>Passive</td><td>PNSC, ESC</td><td>Investigating the influence of RIS's size and location on the secrecy performance</td></tr><tr><td>[131]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td rowspan="2">SR</td><td>Enhancing the security by using RIS as a source of multiplicative randomness</td></tr><tr><td>[277]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Investigating a secure RIS-aided vehicle road cooperation (VRC) system with consecutive artificial noise and index modulation</td></tr><tr><td>[170]</td><td>Continuous</td><td>Spoofing</td><td>Active</td><td>Sum SR</td><td>Detecting spoofing and designing BF to improve secrecy performance</td></tr><tr><td>[146]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>SER</td><td>Reducing the side-lobe energy toward Eve</td></tr><tr><td>[208]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>IP</td><td>Enhancing the secrecy performance by integrating multiple antennas with RIS</td></tr><tr><td>[348]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>IP</td><td>Improving secrecy performance by using friendly jamming and RIS</td></tr><tr><td>[268]</td><td>Continuous</td><td>Spoofing</td><td>Active</td><td>ASR</td><td>Utilizing RIS in increasing the reliability of CF mMIMO systems</td></tr><tr><td>[349]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>Secret key rates</td><td>Analyzing the impact of cooperative multi-Eve scheme against the RIS-secured</td></tr><tr><td>[201]</td><td>Discrete</td><td>Eavesdropping</td><td>Passive</td><td>ESR</td><td>Investigating secure transmission of a LEO satellite using ARIS-equipped HAP</td></tr><tr><td>[191]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>ESR</td><td>Investigating secure massive MIMO RIS-aided system with the CSI imperfections, transceiver hardware impairments, RIS phase noise, and correlated Rayleigh fading</td></tr><tr><td>[238]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>ESC</td><td>Enhancing the PLS of WPC system vis RIS</td></tr><tr><td>[223]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>EC, ECP, ESC</td><td>Investing three secure UAV wireless-powered NOMA transmission modes under Nakagami-m channels and phase compensation errors</td></tr><tr><td>[278]</td><td>Continuous</td><td>Eavesdropping</td><td>Passive</td><td>OP, IP</td><td>Investigating secure RIS-Aided cognitive V2X networks with imperfect CSI over double Rayleigh fading channels</td></tr></tbody></table>

eavesdropper's location was explored. The obtained results illustrated that integrating a RIS-UAV significantly improves the secrecy performance of the LPWAN, enabling reliable long-range transmission.

### C. Secrecy Outage Probability Reduction

By employing thorough techniques, RIS has great promise in reducing the SOP in wireless communication. Through selective signal reflection and BF, RIS directs signals precisely to the intended receiver, minimizing the risk of information leakage. The dynamic adaptability of RIS allows real-time adjustments in response to changing wireless conditions, enhancing secrecy against evolving threats. Intelligent jamming approaches strengthen the communication link, while controlled AN and collaborative RIS networks add complexity to intercepted signals, maintaining confidentiality and reducing the SOP. Utilizing RIS presents an opportunity to increase PLS in wireless communication systems, as highlighted in [171]. One strategy involves leveraging RIS to implement virtual BF, enabling the product of multiple directed beams toward different users. This can potentially enhance the secrecy performance of cellular networks by reducing the signal strength at unintended receivers, thereby confounding the eavesdroppers and decreasing the SOP. Also, RIS can

establish a secure communication zone by directing the signal towards the intended receiver while diverting it away from potential eavesdroppers [208]. Additionally, RIS can serve as a friendly jammer to disrupt eavesdropper signals [147]. The unique capabilities of RIS extend to detecting and identifying eavesdropper locations. By doing so, RIS can assess the proximity of unintended receivers and adjust BF to minimize signal strength at those locations. To secure the transmission link, the RIS was strategically placed near the eavesdropper, effectively shortening information disclosure and heightening the confidentiality of the wireless network [127]. The secrecy performance of a communication system assisted by RIS was investigated in [174] in the presence of spatially random eavesdroppers, where closed-form expressions for the SOP and the eavesdropper SC were derived. To evaluate the SOP, the STAR-RIS-assisted cognitive NOMA-hybrid automatic repeat request (HARQ) network was investigated in [346]. The reviewed performance analysis works on RIS-assisted PLS are summarized in Table VII.

### D. Lessons Learned

This subsection analyzes how the RIS technology improves the performance of the PLS in wireless communication systems. Here are the key takeaways:
* An RIS effectively reduces the SOP by precisely directing signals to intended receivers and minimizing leakage. The strategic placement of RIS creates intelligent environments that enhance link security. Techniques such as intelligent jamming and controlled AN add complexity to intercepted signals, further improving the secrecy performance. This setup is especially effective in maintaining secure communication links in complex scenarios, including urban settings and diverse network configurations.

* Deploying RIS in relay communication systems, including satellite and UAV networks, enhances security against multiple ground eavesdroppers. Incorporating active elements in RIS design addresses the double-fading issues, resulting in smaller RIS sizes without compromising performance. This innovation highlights the potential for more compact and efficient RIS deployments that maintain high security and signal quality, showcasing the versatility of the RIS technology in various applications.

* Conducting thorough performance analyses of RIS-assisted PLS provides valuable insights into SNR improvement, SC enhancement, and the SOP reduction. These analyses demonstrate the feasibility and significance of leveraging the RIS technology to bolster the security of wireless communication systems. Investigating real-world scenarios, such as hardware impairments and spatially random eavesdroppers, emphasizes the practical applicability of the RIS technology. This ensures that theoretical benefits translate into tangible security improvements in real-world deployments, highlighting the crucial role of RIS in enhancing wireless communication security.

* From Table VII, it is clear that most existing research on RIS-assisted PLS performance primarily focuses on passive eavesdropping, where attackers only intercept communication. While mathematically tractable, this approach overlooks the growing threat of active eavesdropping. Active attackers can disrupt communication or manipulate signals, making passive-only analysis insufficient. Moreover, the RIS technology itself can be exploited for jamming by active attackers. Future research needs to prioritize active eavesdropping scenarios to ensure robust security, including developing analytical models for these attacks and designing secure signal processing techniques to detect and mitigate them.

# IX. OPEN RESEARCH CHALLENGES AND FUTURE DIRECTIONS

This section highlights key challenges and future research directions for RIS-assisted PLS in emerging RF and OWC networks aiming at improving wireless network security.

## A. RIS-Assisted Secure Wireless Communications From Optimization Techniques Perspective

The optimization of RIS-assisted secure wireless communications usually involves challenging mathematical problems due to the multiple and typically coupled variables, non-convex objective functions and constraints, the presence of

discrete and continuous decision variables, and the high dimensionality of the optimization problems. As a result, most proposed approaches adopt relaxation, approximation and decomposition techniques which lead to suboptimal performance or result in heuristics without any performance guarantee. This calls for studies on the application of advanced optimization techniques such as global optimization solution methods, i.e., [355], and non-convex non-smooth optimization such as [356], [357]. Metaheuristics on the other hand can tackle various optimization problems without any stringent requirements (e.g., convexity, continuity, and differentiability) for objective functions and constraints, and can cope with high dimensional optimization problems. It is therefore important to examine the application of some recently proposed meta-heuristics [358] in optimizing RIS-assisted secure wireless systems.

## B. RIS-Assisted Secure Wireless Communications via Advanced ML Techniques

Utilizing advanced ML techniques with RIS (see [319] and the references therein) offers a compelling avenue to increase PLS within wireless communication systems. Federated learning, characterized by decentralized model training while preserving data privacy, could be utilized to collectively optimize RIS configurations across distributed network nodes, protecting sensitive information. Graph learning techniques have the potential to facilitate the analysis of complex interaction patterns between RIS components and wireless channels, thereby enabling more accurate prediction and mitigation of potential security vulnerabilities. Transfer learning, involving knowledge transfer from related tasks to enhance RIS configuration optimization for PLS, could expedite the convergence of security-aware RIS designs. Quantum learning techniques, leveraging the computational power of quantum computing, could offer unprecedented capabilities for optimizing RIS configurations and cryptographic protocols, strengthening PLS against quantum-based attacks. Additionally, meta-learning strategies could empower RIS to autonomously adapt and refine their security mechanisms based on past experiences and emerging threats, strengthening the resilience of wireless communication systems against security challenges. Exploring the integrated deployment of these advanced ML techniques with RIS represents a promising future research direction to advance PLS within wireless communication systems.

## C. RIS-Assisted Secure Multiband Networks

The 6G technology will enable the standalone and integrated deployment of various transmission frequencies (including conventional RF, mmWave, THz, and VLC) to offer a trade-off between capacity, latency, network coverage and mobility. However, this comes at the expense of some drawbacks among which wireless security. Malicious users can exploit the different signal propagation characteristics of the various frequency bands for enhanced eavesdropping. A promising avenue for future research studies is to leverage the RIS technology for the security improvement of multiband wireless networks (MWNs) which can be intricate. This is due to the fact
that with the coexistence of multiple spectrum transmissions, employing RIS for security improvement to operate in one frequency band may not necessarily work as well on another spectrum band. Moreover, RISs have different capabilities in various frequency bands. These capabilities affect the role of RIS and the decision variables that need to be optimized in enhancing PLSs. It is therefore important to investigate the role of multiband RISs in PLS.

### D. RIS-Assisted Secure Wireless Communications using a Movable Antenna Technology

Movable antenna (MA) is a novel antenna architecture (see [359] and the references therein) that enables the performance improvement of wireless communication systems by fully leveraging the dynamic transmit/receive antenna placement at positions with more favorable channel conditions, in a confined region<fnref n="3" />. This architecture can be integrated into the RIS technology to ensure the dynamic nature of the latter with a non-uniform activity across all its elements, and thus facilitate more real-time adjustments to wireless communications properties than the fixed position antenna (FPA)-RIS setup. However, obtaining precise CSI at the transmitting/receiving ends or optimizing antenna positions that yields the best communication performance can be very challenging. There is limited research on the adoption of RIS in MA-based wireless systems, let alone in the context of PLS. Exciting areas worth investigating include jointly optimizing MA position, power allocation, and RIS deployment and parameter(s), such as phase shift for RF-based RIS and orientation angles for optical RIS tuning to maximize PLS. Exploring this research direction has the potential to bring significant advancements in future wireless networks while enabling secure and reliable networks for practical scenarios.

### E. RIS-Assisted Secure Systems in Generalized Fading

Exploring the potential of RIS to improve the information-theoretic security of wireless systems in generalized fading scenarios represents a promising direction for future studies. The generalized fading models such as $\alpha$-$\mu$, $\kappa$-$\mu$ and $\eta$-$\mu$, adequately fit real-time experimental data and can be used to characterize small-scale fading in the mmWave and THz bands where a large contiguous bandwidth is available and can be exploited to support the demand for bandwidth-hungry applications in ultra-dense networks. As in the case of classical fading models (Rayleigh, Rician, Nakagami-m, etc...), wireless transmissions over generalized fading channels are susceptible to security vulnerabilities. In this context, the deployment of RIS wireless systems subject to generalized fading emerges as an appealing direction for future investigations. However, it is worth noting the analytical intricacies of obtaining the exact statistics of RIS-aided secure systems in such fading models, let alone the various exact performance measures. Addressing these challenges is crucial and will therefore constitute an advancement to the current state-of-the-art.

### F. RIS-Assisted Secure Communications With Other Emerging Wireless Technologies

This subsection highlights the key challenges and future research directions for emerging applications that have not yet been explored in terms of information-theoretic security through the RIS technology.

1. **RIS-Assisted Secure CoMP Communications:** RIS-assisted secure coordinate multi-point (CoMP) Communications are considered an open research area that aims to enhance the performance and security of wireless networks. By integrating RIS within the CoMP framework, the technology endeavors to optimize parameters such as signal strength, coverage, and overall system capacity while simultaneously addressing issues such as interference mitigation and signal confidentiality enhancement. Key areas of research focus include the development of efficient strategies for RIS deployment and joint optimization of CoMP and RIS to increase the security level. Despite the complexity of such challenges, RIS-assisted secure CoMP communications maintain significant promise in securing wireless communication networks by offering enhanced performance and security capabilities that align with the evolving requirements of next-generation applications and services.

2. **RIS-Assisted Secure Blockchain Technology:** Integrating RIS into secure blockchain technology is an innovative strategy for reinforcing the security and confidentiality of distributed ledgers [363]. RIS actively plays a role in mitigating potential attacks, such as jamming from malicious nodes, by intelligently redirecting and optimizing communication links. Consequently, the security of blockchain technology is improved, establishing a more robust and reliable framework. Moreover, the adaptability and flexibility of RIS align with the decentralized nature of blockchain, offering an additional layer of security. Despite existing challenges in deployment and integration, the prospective advantages of RIS-assisted secure blockchain technology lie in its ability to elevate the reliability and robustness of decentralized systems, resulting in secure and efficient blockchain applications.

3. **RIS-Assisted Secure RSMA-based Systems:** NOMA has emerged as a key-enabling technology for 5G networks [364]. However, major challenges such as hardware complexity, receiver design, error propagation in SIC just to name a few, have hampered its development for 5G and beyond wireless systems. To this end, rate splitting multiple access (RSMA) is envisioned as a key-enabling multiple-access scheme that addresses the massive connectivity problem by accommodating different users in future heterogeneous networks. Incorporating RIS into RSMA-based systems may be used to improve the network performance in the context of PLS. By taking advantage of the reflective elements in the RIS technology, it is feasible to establish a highly directional and controllable wireless transmission environment. This capability may facilitate the improvement of the legitimate user's signal strength or the attenuation of the malicious signal, thereby enhancing the overall wireless security of practical RSMA-based systems without the need for extra processing, and signaling. This is worthwhile to be explored as a potential direction for future research studies.

<footnote n="3">³A similar approach to MA is the fluid antenna (FA) technology wherein an antenna can freely switch positions in a fixed-length linear space in search of the strongest signal [360]–[362].</footnote>
4) RIS-Assisted Secure AR and VR Communications:

AR and VR applications require seamless communications with negligible latency and ultra-high bandwidth that can be achieved via abundant spectrum bands, such as mmWave and THz bands, at the expense of limited range and high blockage by physical barriers. To this end, ensuring the wireless security of such applications is a challenging task. A potential research direction on RIS-aided secure AR and VR communications may focus on leveraging RIS to enhance the security of communication channels in AR and VR applications. The goal is to strategically deploy RIS elements to ensure the confidentiality of sensitive data transmitted in immersive environments. The investigation will address challenges such as adapting RIS configurations to the dynamic nature of AR and VR and balancing security needs with low-latency communication.

5) RIS-Assisted Secure Under-water Communications:

Achieving secure wireless communications in underwater is a necessity for governments, commercial companies, and the military. This is because underwater wireless communications play an important role in both civil applications such as oil and gas exploration and military applications. Exploring the potential of securing both underwater OWCs that has a medium communication range that spans between 50-100 meters and underwater RF wireless communications that is suitable for short-distance propagation of around 10 meters can be an attractive area for future research. One possible way to attain this is by mounting RISs on underwater entities (e.g., autonomous underwater vehicles, submarines, divers, etc.), at the sea level, or at the ground level under the sea while employing one of PLS techniques.

6) *Mixed RIS/FSS-Assisted Secure Wireless Networks:* Despite providing more security and interference immunity, the users’ confidentiality of a frequency selective surface (FSS)-aided wireless communication system may still be compromised through the FSS filters which may expose users’ sensitive data including location information, behavior patterns, etc., by revealing the users’ communication frequency usage. In this context, the deployment of RIS in FSS-assisted communication networks emerges as an appealing research direction for future studies to mitigate users’ security. Although both the RIS and FSS belong to the family of intelligent surfaces, they differ in their structure and working principle. To this end, the adoption of RIS in the present context is undeniably of utmost interest for the development of 6G communication networks since it is likely to bring forth design issues as well as challenges on the optimization of the signal quality and coverage.

X. CONCLUSION

This paper has provided a comprehensive review on the up-to-date research for the information-theoretic security of RIS-enabled future wireless systems. To begin with, an overview of the PLS fundamentals has been presented by focusing on the various types of attacks in PLS, the techniques used to achieve PLS, and the secrecy performance metrics. Moreover, the working principles and architecture of the RIS technology have been explored followed by its corresponding deployment

strategies for future wireless communication systems. Besides, the RIS technology suited for OWC has also been presented. Subsequently, the RIS-enabled PLS scenarios and techniques in both RF and OWC systems have been discussed. Furthermore, the state-of-the-art optimization techniques for PLS have been reviewed and some existing optimization methods for secrecy performance maximization have been summarized. To address the complexity issues associated with the rapid increase in the number of interactions between users and infrastructures in future wireless networks, the adoption of ML in RIS-assisted PLS-based systems has been well investigated. A comprehensive discussion on the performance analysis of RIS-assisted PLS-based wireless systems has been presented, and useful insights into the adoption of the RIS technology for performance improvement have been provided. Finally, some insightful open research challenges have been proposed and thoroughly discussed, and corresponding future research directions have ensued to further close the knowledge gap towards the development of forthcoming wireless technologies. We hope that this survey paper will serve as a valuable resource for researchers and practitioners in an effort to bring the deployment of RIS-assisted PLS in emerging wireless systems closer to reality.

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