The rapid development of 5G networks and the anticipation of 6G technologies have ushered in an era of highly customizable network environments facilitated by the innovative concept of network slicing. This technology allows the creation of multiple virtual networks on the same physical infrastructure, each optimized for specific service requirements. Despite its numerous benefits, network slicing introduces significant security vulnerabilities that must be addressed to prevent exploitation by increasingly sophisticated cyber threats. This review explores the application of cutting-edge technologies—Artificial Intelligence (AI), specifically Machine Learning (ML), Software-Defined Networking (SDN), and Network Functions Virtualization (NFV)—in crafting advanced security solutions tailored for network slicing. AI’s predictive threat detection and automated response capabilities are analysed, highlighting its role in maintaining service integrity and resilience. Meanwhile, SDN and NFV are scrutinized for their ability to enforce flexible security policies and manage network functionalities dynamically, thereby enhancing the adaptability of security measures to meet evolving network demands. Thoroughly examining the current literature and industry practices, this paper identifies critical research gaps in security frameworks and proposes innovative solutions. We advocate for a holistic security strategy integrating ML, SDN, and NFV to enhance data confidentiality, integrity, and availability across network slices. The paper concludes with future research directions to develop robust, scalable, and efficient security frameworks capable of supporting the safe deployment of network slicing in next-generation networks.

The advance of industrialization regarding the optimization of production to obtain greater productivity and consequently generate more profits has led to the emergence of Industry 4.0, which aims to create an environment called smart manufacturing. On the other hand, the Internet of Things is a global network of interrelated physical devices, such as sensors, actuators, intelligent applications, computers, mechanical machines, objects, and people, becoming an essential part of the Internet. These devices are data sources that provide abundant information on manufacturing processes in an industrial environment. A concern of this type of system is processing large sets of data and generating knowledge. These challenges often raise concerns about security, more specifically cybersecurity. Good cybersecurity practices make it possible to avoid damage to production lines and information. With the growing increase in threats in terms of security, this paper aims to carry out a review of existing technologies about cybersecurity in intelligent manufacturing and an introduction to the architecture of the IoT and smart manufacturing.

Reservoirs are fundamental for water and energy supply but vulnerable to impacts including climate change. This paper outlines the steps in the development of a model to predict how climate, land use and hydrological change could affect the physiochemical and ecological quality of reservoirs in Portugal's Douro region. Climatic data will be downscaled for subsequent finer spatial scale models to develop scenarios and outputs. Field observations and satellite imagery analysis will create dynamic maps providing data on change in land use and vegetation cover, while Artificial Neural Networks will determine how climate, land use and vegetation cover change may influence catchment hydrology. Data from field surveys of biological indicators, greenhouse gas emissions plus additional research will be applied in the Stochastic Dynamic Methodology, a sequential modelling process based on statistical parameter estimation, developed to predict and model physiochemical and ecological changes in reservoirs. This interdisciplinary approach will provide vital modelling tools for end users essential for water resource management in Portugal and to comply with the EU Water Framework Directive.

Inter-organizational strategic alliances, in which networks of cooperation stand out, have proved to be a good model to provide more competitive organizations. However, there are still shortcomings concerning models and supporting technologies that help the creation of inter-organizational arrangements. This paper presents a conceptual model for the establishment of cooperation networks, an information system that supports the proposed model and, finally, the results of a case study in the tourism sector.