In an era dominated by digitalization in corporate strategies, the effectiveness of network infrastructures constitutes the foundation upon which enterprises build their businesses. Within this context, Intent-Based Networking (IBN) emerges as a networking paradigm that addresses the need for autonomous and intelligent systems, shifting network management from static to dynamic and automated processes. Despite its significant advancements in network automation, IBN introduces new complexities and challenges, particularly concerning the assessment of reliability or trustworthiness. Formulating intent without thorough investigation of users’ intentions could potentially lead to deliberate network sabotage, denial of services, data breaches, and privilege escalations, thereby posing significant risks to enterprise networks. To bridge this gap, this study proposes a novel Malicious Intent Detection (MID) module within the IBN framework to construct a security knowledge base for accurately classifying enterprise users’ intentions. Specifically, it detects malicious expressions directly during the intent processing stage, thereby preventing the formulation of disruptive network configurations or policies derived from malicious intents. The obtained results demonstrate the effectiveness of the proposed solution, with the ability to detect 94% of malicious intentions and achieve an accuracy of up to 93%.

The Social Internet of Things is gaining momentum thanks to its unique capability of i) autonomously building social relationships among smart objects and ii) supporting the novel services within the Social Network. During the service provisioning, the Trust Management System is in charge of selecting suitable objects able to accomplish the requested services. In this context, available solutions present two relevant issues to be solved. First, they generally assume to select social objects that only achieve higher trustworthiness without considering their actual computing capabilities. Indeed, it would significantly compromise the Quality of Experience in the Social Network of objects. Second, they assume to implement this task directly within constrained devices, becoming unpractical considering their limited computational and storage capabilities. To improve and speed up service provisioning, this paper proposes a novel Trust Management System scheme that fairly distributes service requests by jointly considering the trustworthiness and resource capabilities of available objects. This Trust Management System has been designed to exploit fog computing to efficiently handle the whole process of service provisioning in real-world deployments while relieving constrained devices from all processing and storage efforts. Its behavior is investigated through computer simulations. Obtained results demonstrated that the conceived approach outperforms baseline solutions in terms of latency, fairness in services distribution, and responsiveness in malicious nodes' detection.

The adoption of the Narrowband-Internet of Things technology in satellite communications intends to boost Internet of Things services beyond the boundaries imposed by the current terrestrial infrastructures. Apart from link-level studies in the scientific literature and preliminary 3GPP technical reports, the overall debate is still open. To provide a further step forward in this direction, the work presented herein pursues a novel service-oriented methodology to design an effective solution, meticulously stitched around application requirements and technological constraints. To this end, it conducts link-level and system-level investigations to tune physical transmissions, satellite constellation, and protocol architecture, while ensuring the expected system behavior. To offer a real smart agriculture service operating in Europe, the resulting solution exploits 24 low-Earth orbit satellites, grouped into eight different orbits, moving at an altitude of 500 km. The configured protocol stack supports the transmission of tens of bytes generated at the application layer, by also counteracting the issues introduced by the satellite link. Since each satellite has the whole protocol stack onboard, terminals can transmit data without the need for the feeder link. This ensures communication latencies ranging from 16 to 75 min, depending on the served number of terminals and the physical transmission settings. Moreover, the usage of the early data transmission scheme reduces communication latencies up to 40%. These results pave the way toward the deployment of an effective proof of concept, which drastically reduces the time to market imposed by the current state of the art.

In the Social Internet of Things paradigm, the Trust Management System computes trust values of involved social objects, identifies trusted relationships, and selects the most suitable object able to provide a target service. State-of-the-art mechanisms conceived to address these tasks generally avoid considering the actual availability of social objects and demand the implementation of complex algorithms to constrained nodes. This work presents a novel multi-tiered and fog-based Social Internet of Things architecture to solve these open issues, ensuring fast service provisioning, high scalability, fault tolerance, and security. On the one hand, the Trust Management System hosted at the first fog layer of the architecture jointly addresses the trustworthiness of service providers and monitors the re-source availability exposed by social objects, thus simplifying the forwarding of service requests to trusted and unloaded nodes. From another hand, to securely implement advanced services at a large scale, a second fog layer exploits a Blockchain-based storage for sharing services, relationships, and trust values across organizations and service domains. Computer simulations demonstrate the effectiveness of the proposed architecture in a realistic Social Internet of Things while showing the performance gain obtained against a baseline approach.

Satellite Communication is expected to play a leading role in 5G & Beyond networks. Current studies, however, focus the attention on physical and link-level aspects, while ignoring to evaluate system-level performance. This paper presents a novel simulation tool, conceived as a new module for the open-source 5G-air-simulator, modeling NB-IoT satellite-based communication systems. Specifically, it implements several link-to-system abstraction models, the cell selection procedure, and a configurable satellite constellation. Furthermore, these essential features are successfully integrated within the rest of the 5G-air-simulator, thus offering the opportunity to test flexible network deployments (e.g., by varying the number and the distribution of users) under different application statistics. To demonstrate the actual effectiveness of the developed tool, this work also presents a preliminary performance assessment of an NB-IoT satellite-based communication system enabling reference monitoring scenarios.