The advent of 5th Generation (5G) networks has introduced the strategy of network slicing as a paradigm shift, enabling the provision of services with distinct Quality of Service (QoS) requirements. The 5th Generation New Radio (5G NR) standard complies with the use cases Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), which demand a dynamic adaptation of network slicing to meet the diverse traffic needs. This dynamic adaptation presents both a critical challenge and a significant opportunity to improve 5G network efficiency. This paper proposes a Deep Reinforcement Learning (DRL) agent that performs dynamic resource allocation in 5G wireless network slicing according to traffic requirements of the 5G use cases within two scenarios: eMBB with URLLC and eMBB with mMTC. The DRL agent evaluates the performance of different decoding schemes such as Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA), and Rate Splitting Multiple Access (RSMA) and applies the best decoding scheme in these scenarios under different network conditions. The DRL agent has been tested to maximize the sum rate in scenario eMBB with URLLC and to maximize the number of successfully decoded devices in scenario eMBB with mMTC, both with different combinations of number of devices, power gains and number of allocated frequencies. The results show that the DRL agent dynamically chooses the best decoding scheme and presents an efficiency in maximizing the sum rate and the decoded devices between 84% and 100% for both scenarios evaluated. • 5G Network Slicing Optimization. • eMBB, URLLC, and mMTC Coexistence. • OMA, NOMA, RSMA. • Deep Reinforcement Learning. • The maximization of the sum rate on the scenario eMBB with URLLC and the maximization of the number of successfully decoded devices on the scenario eMBB with mMTC.

Cyberattacks exploit deceptions involving the Domain Name Service (DNS) to direct users to fake websites, such as typosquatting attacks, which exploit natural typographical errors, and homograph attacks, where different Unicode characters resemble the legitimate ones.

In an era marked by escalating cyber threats, the need for robust cybersecurity measures is paramount, especially for Higher Education Institutions (HEIs). As custodians of sensitive information, HEIs must ensure secure channels for data transmission to protect their stakeholders. These institutions should increase their cyber resilience, recognizing the heightened risk they face from cybercriminal activities. A breach in an HEI’s cybersecurity can have severe consequences, ranging from data confidentiality breaches to operational disruptions and damage to institutional reputation. This paper conducts a comprehensive evaluation of the cybersecurity mechanisms in HEIs within Poland. The focus is on assessing the adoption of important web security protocols—Hyper Text Transfer Protocol Secure (HTTPS) and Domain Name System Security Extensions (DNSSEC)—and the implementation of security headers on HEI websites. This study aims to provide a snapshot of the current cyber defense maturity in HEIs and to offer actionable insights for enhancing web security practices. The findings indicate a high adoption rate of HTTPS among HEIs, yet reveal significant gaps in web security practices. Also, there is a low adherence to security headers and an absence regarding DNSSEC implementation across the surveyed institutions. These results highlight crucial areas for improvement and underscore the need for HEIs in Poland to strengthen their web security measures, safeguarding their data and enhancing the overall cybersecurity resilience.

Monitoring security and quality of service is essential, due to the rapid growth of the number of nodes in wireless networks. In healthcare/industrial environments, especially in wireless body area networks (WBANs), this is even more important. Because the delays and errors can directly affect patients'/scientists' health. To increase the Monitoring Quality of Services (MQoS) in WBANs, a secure medium access control (MAC) protocol needs to be developed to provide optimal services. This article provides a comprehensive review of MAC protocols in WBANs with a technical security analysis approach. Time-based, contention-based, and hybrid protocols are compared in this article, regarding MQoS and their security vulnerabilities. We have considered delay, packet loss, and energy consumption as performance evaluation criteria in WBANs, which may be degraded under a cyberattack. This work shows that there is a research gap in the literature, which is the failure of covering security and privacy issues in the MAC layer protocols.

Recent studies in information computation technology (ICT) are focusing on Next-generation networks, SDN (Software-defined networking), 5G, and 6G. Optimal working mode for device-to-device (D2D) communication is aimed at improving the quality of service with the frequency spectrum structure is of research areas in 5G. D2D communication working modes are selected to meet both the predefined system conditions and provide maximum throughput for the network. Due to the complexity of the direct solutions, we formulated the problem as an optimization problem and found the optimal working modes under different parameters of the system through extensive simulations. After determining the links’ optimal modes, we calculated the network throughput; because of selecting the best working modes, we obtained the highest throughput. A major finding from this research is that D2D communication pairs are more inclined to use full-duplex (FD) mode in short distances to meet system requirements, and so most communications take place in FD mode at these distances. According to these results, using FD communication at short distances offers better conditions and Quality of service (QoS) than QoS-D2D method.