Recent advances in quantum computing have prompted urgent consideration of the migration of classical cryptographic systems to post-quantum alternatives. However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without the actual implementation of quantum-resistant cryptography. On the other hand, PQC algorithms come with complexity and long processing times, which may impact the quality of service (QoS) of many applications. Therefore, PQC-based protocols with practical implementations across various applications are essential. This paper introduces a new framework for PQC standalone and PQC–AES (Advanced Encryption Standard) hybrid public-key encryption (PKE) protocols. Building on prior results, we focus on securing applications such as file transfer, video streaming, and chat-based communication using enhanced PQC-based protocols. The extended PQC-based protocols use a sequence number-based mechanism to effectively counter replay and man-in-the-middle attacks and mitigate standard cybersecurity attack vectors. Experimental evaluations examined encryption/decryption speeds, throughput, and processing overhead for the standalone PQC and the PQC–AES hybrid schemes, benchmarking them against traditional AES-256 in an existing client–server environment. The results demonstrate that the new approaches achieve a significant balance between security and system performance compared to conventional deployments. Furthermore, a comprehensive security analysis confirms the robustness and effectiveness of the proposed PQC-based protocols across diverse attack scenarios. Notably, the PQC–AES hybrid protocol demonstrates greater efficiency for applications handling larger data volumes (e.g., 10–100 KB) with reduced latency, underscoring the practical necessity of carefully balancing security and operational efficiency in the post-quantum migration process.

Demands for high-speed wireless connectivity are pushing the boundaries of Wireless Local Area Networks (WLANs), prompting a transition towards Terahertz (THz) technology for 6G networks. THz technology is capable of supporting higher data rates and lower latency, enabling the miniaturization and denser placements of Access Points (APs), particularly in urban environments. Joint transmission strategies, coordinating data from multiple APs, can further improve THz network performance and reliability. Despite its advantages, THz signals face challenges with signal penetration and attenuation. To tackle these issues, Intelligent Reflecting Surfaces (IRS), a planar surface made with reconfigurable meta-material elements, have emerged as a solution with the abilities to create beyond Line-of-Sight (LoS) communication and passive beamforming. In this paper, we study the channel estimation and resource allocation problem with considering the user mobility and increased system complexity. A combined clustering and Kalman Filtering (KF) approach is proposed to continuously estimate user statuses and efficiently organize network elements. The simulation results demonstrate that our approach markedly enhances the performance of joint transmission and reduces the overhead associated with channel estimation, thereby highlighting the potential of integrating THz joint transmission and IRS in future WLANs.

Networking services may be broken down in a disaster situation while people in the disaster area(s) strongly demand networking services for both communication and information sharing among users. This requires the fast restoration of networking services to fulfil the demand–supply gap. Although there are a number of studies on restoring communication and networking in disasters, few studies have explicitly examined the service availability during the temporary and partial recovery process of network restoration. From the perspective of users in the disaster area, it is important to be able to communicate or share information with people whenever they want/need to do so. Therefore, partial and local recovery of the networking services also plays an important role for improving service availability in the disaster situations. To assess the restoration effectiveness of networking services with a measure of user satisfaction level, we propose to use instant networking service availability (I-NSA), a novel metric, and we examine the effectiveness of networking service restoration solutions using the metric. I-NSA allows us to clearly express the instant availability of networking services that drastically changes with the elapsed time from the disaster occurrence in disaster areas. This paper examines the effective improvement of I-NSA when Local-and-Instant Clouds (LI-Clouds) are applied to the disaster situation. LI-Cloud has been designed and practically developed to provide deployable networking services to users. We verify that LI-Cloud enables significant improvement on the I-NSA performance in the fast restoration of networking services.

Unmanned aerial vehicles (UAVs) are commonly used in disaster recovery efforts to confirm the extent of the damage caused by a large-scale disaster and to ensure that adequate information about the affected area is gathered. UAV usage in a disaster situation is not limited to information gathering, but its functions further extend to network communication functions such as a communication relay, mobile base station, etc. Conversely, using UAVs as communication relays or base stations (e.g., as a temporary mobile base station) is subject to some limitations such as bad weather and limited energy, which affect the timely collection and delivery of information to and from a disaster area. Therefore, an approach to improve the information collection and delivery in a disaster area while ensuring urgent network restoration is necessary. In this paper, we introduce a practical approach to deploying a drone-based message ferry to improve the timely collection and delivery of information in a disaster situation. Specifically, a locally accessible cloud system (LACS), which we previously developed for urgent local network restoration in a disaster affected area, is attached to a drone to form a message ferry. In order to improve the information collection and delivery, the message ferry is deployed from the local headquarters (i.e., local government office or disaster response coordination center) to carry information to and from a standalone LACS installed at each disaster shelter. We measure the achievable data rate of inter-LACS data transfer (i.e., message ferry and a standalone LACS) through experiment. Thereafter, we estimate and confirm the effective transmission speed to transfer data from the local headquarters to the disaster shelters using average achievable data rate obtained from the experiment in order to extend the LACS services and functions. Our experimental results and analysis suggest that the proposed message ferry is more advantageous to transfer a large amount of data (e.g., 300 MB) at a high speed in the hundred meter to ten kilometer range.

For a millimeter wave (mmWave) intelligent re-configurable surface (IRS)-MIMO system, if it can correctly detect the interference occurrence and their locations, the patterns of interference signal can be collected and learned using machine learning for the prediction of interference arrival. With the information of interference location and activity pattern, the capacity of the system can be largely improved using many techniques such as beamforming, interference cancellation, and transmission scheduling. This paper aims to detect interference occurrence using a low-complexity MUSIC (MUSIC: multiple signal classification) spectrum-based method, and then localize their sources for mmWave IRS-MIMO system. The MUSIC spectrum of wireless system can be regarded as somehow the ‘signature’ related to the signals transmitted from different users or interference. We utilize such property to detect the occurrence of interference, and then localize their sources in a low-complexity way. Finally, the pattern of interference occurrence can be learned to predict the interference arrival from the collected data. This paper also proposed an efficient probabilistic neural network (PNN)-based predictor for the interference arrival prediction and showed its prediction accuracy. From simulated results, our proposed method can achieve the correct results with the accuracy near to 100% when the fingerprint samples is over 10. In addition, the localization error can be within 1 m with more than 65% and 43% for Y-axis and X-axis, respectively. Finally, based on the results of the interference occurrence, the proposed PNN-based predictor for the interference arrival prediction can capture correctly the similar distribution function of the coming continuous idle status.

Recent advances in quantum computing have prompted urgent consideration for the migration of classical cryptographic systems to post-quantum alternatives. However, it is impossible to fully understand the impact that migrating to current Post-Quantum Cryptography (PQC) algorithms will have on various applications without actual implementation of quantum-resistant cryptography. On the other hand, PQC algorithms come with complexity and long processing times, which may impact the Quality of Service (QoS) of many applications. Therefore, PQC-based protocols with practical implementation across various applications are essential. This paper introduces a new framework for PQC standalone and PQC-AES (Advanced Encryption Standard) hybrid Public Key Encryption (PKE) protocols. Building on prior results, we focus on securing applications such as file transfer, video streaming, and chat-based communication using enhanced PQC-based protocols. The extended PQC-based protocols use a sequence number-based mechanism to effectively counter replay and man-in-the-middle attacks and mitigate standard cybersecurity attack vectors. Experimental evaluations examined encryption/decryption speeds, throughput, and processing overhead for these standalone PQC and PQC-AES hybrid schemes, benchmarking them against traditional AES-256 in an existing client-server environment. The results demonstrate that the new approaches achieve a significant balance between security and system performance compared to conventional deployments. Furthermore, the comprehensive security analysis confirms the robustness and effectiveness of the proposed PQC-based protocols across diverse attack scenarios. Notably, the PQC-AES hybrid protocol demonstrates greater efficiency for applications handling larger data volumes (e.g., 10–100 KB) with reduced latency, underscoring the practical necessity of carefully balancing security and operational efficiency in the post-quantum migration process.