DIT - RYSC - Capítulos de monografías

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Using CTI Data to Understand Real World Cyberattacks
(IEEE, 2023-03-23) Allegretta, Mauro; Siracusano, Giuseppe; González Sánchez, Roberto; Vallina Rodríguez, Pelayo; Gramaglia, Marco; European Commission; Ministerio de Asuntos Económicos y Transformación Digital (España)
The forensic analysis of Cyber Threat Intelligence (CTI) data is of capital importance for businesses and enterprises to understand what has possibly gone wrong in a cybersecurity system. Moreover, the fast evolution of the techniques used by cybercriminals requires collaboration among multiple partners to provide efficient security mechanisms. STIX has emerged as the industrial standard to share CTI data in a structured format, allowing entities from over the world to exchange information to broaden the knowledge base in the area. In this work, we shed light on the type of information contained in these datasets shared among partners. We analyze a large real-world STIX dataset and identify trends for the reporting of CTI data. Then, we deep dive into two kinds of attack patterns found in the dataset: Command & Control and Malicious Software Download. We found the data is not only useful for forensic analysis but can also be used to improve the protection against new attacks.
An NFV system to support service provisioning on UAV networks
(Universidad de La Coruña, 2021-10-27) Nogales Dorado, Borja; Vidal Fernández, Iván; Sánchez Agüero, Víctor; Valera Pintor, Francisco; González Blázquez, Luis Félix; European Commission; Agencia Estatal de Investigación (España)
In this presentation, we will first describe the design and implementation of an NFV system capable of deploying moderately complex network services over a wireless ad-hoc network of resource-constrained compute nodes. The system design targets aerial networks built by Unmanned Aerial Vehicles (UAVs), and it relies on container virtualization to support the execution of network functions within constrained environments, as well as on mobile ad-hoc networking to support the underlying end-to-end network communications [1]. The presentation will also cover the implementation experience from developing this NFV system, which is based on relevant and widely-adopted open-source technologies in the NFV arena such as ETSI Open-Source MANO (OSM) and OpenStack. In addition, we will present the details concerning the integration of this system into a distributed NFV testbed spanning three different remote sites in Spain, i.e., Universidad Carlos III de Madrid (UC3M), Universidad Politécnica de Cataluña (UPC), and Universidad del País Vasco (UPV-EHU). The goal of this testbed is to explore synergies among NFV, UAVs, and 5G vertical services, following a practical approach primarily governed by experimentation. To showcase the potential of this testbed to support vertical services, we will present three different use cases that have been realized as part of our prior research work: i) the automated deployment of an IP telephony service on a delimited geographic area, using a network of interconnected UAVs [2] (noteworthily, this work was awarded by ETSI as the best proof-of-concept demonstration with OSM during the OSM Release Eight cycle [3]); ii) the realization of a smart farming vertical service [4]; and iii) a public-safety vertical use case, which uses aerial and vehicular NFV infrastructures to monitor traffic conditions and handle emergency situations [5]. This latter involves an international collaboration with the Instituto de Telecomunicações of Aveiro, which operates a vehicular NFV infrastructure. Finally, the presentation will tackle the standardization challenges related with the future view of a decentralized and flexible MANO framework, capable of supporting the operation of cost-effective, reliable services beyond the edge of the telecommunication operator infrastructures. In this view, multiple stakeholders would collaboratively provide a wide range of heterogeneous compute-connect devices (e.g., end-user terminals, CPEs, or UAV swarms). These devices might exist and be opportunistically used, or they could otherwise be deployed on-demand by those stakeholders, contributing to the availability of a potentially unlimited pool of network, computing, and storage resources beyond the network edge. This view introduces several standardization challenges to the NFV MANO framework in terms of interoperation, flexibility, robustness, and security. These challenges have been presented at the NFV Evolution1 event organized by ETSI, and will build the basis of our future work in this research line.
Trading accuracy for privacy in machine learning tasks: an empirical analysis
(IEEE, 2022-03-22) Prodomo, Vittorio; González Sánchez, Roberto; Gramaglia, Marco; European Commission
Different kinds of user-generated data are increasingly used to tailor and optimize, through Machine Learning, the operation of online services and infrastructures. This typically requires sharing data among different partners, often including private data of individuals or business confidential data. While this poses privacy issues, the current state-of-the-art solutions either impose strong assumptions on the usage scenario or drastically reduce the data quality. In this paper, we evaluate through a generic framework the trade-offs between the accuracy of Machine Learning tasks and the achieved privacy (measured as similarity) on the input data, discussing trends and ways forward.
Data collection and utilization framework for edge AI applications
(IEEE, 2021-07-08) Rexha, Hergys; Lafond, Sébastien; European Commission
As data being produced by IoT applications continues to explode, there is a growing need to bring computing power closer to the source of the data to meet the response-time, power dissipation and cost goals of performance-critical applications in various domains like Industrial Internet of Things (IIoT), Automated Driving, Medical Imaging or Surveillance among others. This paper proposes a data collection and utilization framework that allows runtime platform and application data to be sent to an edge and cloud system via data collection agents running close to the platform. Agents are connected to a cloud system able to train AI models to improve overall energy efficiency of an AI application executed on a edge platform. In the implementation part we show the benefits of FPGA-based platform for the task of object detection. Furthermore we show that it is feasible to collect relevant data from an FPGA platform, transmit the data to a cloud system for processing and receiving feedback actions to execute an edge AI application energy efficiently. As future work we foresee the possibility to train, deploy and continuously improve a base model able to efficiently adapt the execution of edge applications.
An Intelligent Edge-based Digital Twin for Robotics
(IEEE, 2020-12-07) Girletti, Luigi; Groshev, Milan; Magalhaes Guimaraes, Carlos Eduardo; Bernardos Cano, Carlos Jesús; Oliva Delgado, Antonio de la; European Commission
Digital Twin is one of the use cases targeted by the fourth industrial revolution (Industry 4.0), which, through the digitalization of the robotic systems, will enable enhanced automation and remote controlling capabilities. Building upon this concept, this work proposes a solution for an Edge-based Digital Twin for robotics, which leverages on the cloud-to-things continuum to offload computation and intelligence from the robots to the network. This imposes stringent requirements over the communication technologies which are fulfilled by relying on 5G. This solution is implemented in an E2E scenario combining the cloud-to-things continuum, 5G connectivity and intelligence capabilities and validated through a set of experimental evaluations. Results show not only that offloading the robot's functions to the edge is feasible when supported by the 5G connectivity, but also the benefits of introducing intelligence and automation.
The touristic sector in the 5G technology era: the 5G-TOURS project approach
(IEEE, 2021-03) Vignaroli, Luca; Gramaglia, Marco; Fuentes, Manuel; Casella, Antonino; Odarchenko, Roman; Natale, Lorenzo; Altman, Baruch; D'Andria, Francesco; European Commission
5G mobile networks are designed to fulfill very stringent requirements and support new vertical use cases. This transition to a vertical oriented delivery model will have a strong impact in the touristic sector. In this context, the "touristic city node" of 5G-TOURS, built in the city of Turin, aims at exploiting the potential of the media vertical. The objective is to develop an innovative tourism concept based on complementary and linked trials for five specific use cases. The trials will promote an overall integrated indoor/outdoor immersive experience to the visitors using any possible device, enhancing the accessibility to the technology especially for disadvantaged and disabled people. They will also utilize 5G to drive "remote tourism" based on AR/VR experiences and bridge the gap between the physical and virtual worlds for tourism. This paper provides an overview of the 5G technology deployed in the touristic node, explaining the different services to be provided and discussing the need of 5G technology to support this vision. This work also assesses the business potential of each of the considered use cases, corroborating their potential in the context of future network services.
On the Integration of AI/ML-based scaling operations in the 5Growth platform
(IEEE, 2020-11-09) Baranda, Jorge; Mangues-Bafalluy, Josep; Zeydan, Engin; Vettori, L.; Martínez, Ricardo; Li, Xi; Garcia Saavedra, Andres; Chiasserini, C. F.; Casetti, C.; Tomakh, K.; Kolodiazhnyi, O.; Bernardos Cano, Carlos Jesús; European Commission; Ministerio de Economía y Competitividad (España)
The automated assurance of vertical service level agreements (SLA) is a challenge in 5G networks. The EU 5Growth project designs and develops a 5G End-to-End service platform that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques for any decision-making process in the management and orchestration (MANO) stack. This paper presents the detailed architecture and first prototype of the 5Growth platform taking AI/ML-based network service auto-scaling decisions. This also includes the modification of the ETSI network service descriptors for requesting AI/ML-based decisions for orchestration problems and the integration of a data engineering pipeline for real-time data gathering and model execution. Our evaluation shows that AI/ML-related service handling operations (1&-2 s.) are well below instantiation/termination procedures (80/60 s., respectively). Furthermore, online classification can be performed in the order of hundreds of milliseconds (600 ms).
NFV Service Federation: enabling Multi-Provider eHealth Emergency Services
(IEEE, 2020-07-06) Baranda, Jorge; Mangues-Bafalluy, Josep; Vettori, L.; Martínez, R.; Antevski, Kiril; Girletti, Luigi; Bernardos Cano, Carlos Jesús; Tomakh, K.; Kucherenko, D.; Landi, Giada; Brenes, Juan; Li, Xi; Costa-Pérez, Xavier; Ubaldi, F.; Imbarlina, G.; Gharbaoui, M.; European Commission
One of the key challenges in developing 5G/6G is to offer improved vertical service support providing enlarged service flexibility, coverage and connectivity while enhancing the business relations among different stakeholders. To address this challenge, Network Service Federation (NSF) is a required feature to enable the deployment and the management of vertical services that may span multiple provider domains owned by different operators and/or service providers. In this demonstration, we show our proposed NSF solution to dynamically deploy an eHealth network service across multiple provider domains at different locations.
A monitoring framework for multi-site 5G platforms
(IEEE, 2020-06-15) Pérez, Ramón; García Reinoso, Jaime José; Zabala Orive, Aitor; Serrano Yáñez-Mingot, Pablo; Banchs Roca, Albert; European Commission
The fifth generation (5G) of mobile networks will have to accommodate different types of use cases, each of them with different and stringent requirements and key performance indicators (KPIs). To support this, apart from novel technologies such as network slicing or artificial intelligence, 5G will require a flexible and efficient monitoring system. The collected metrics serve to optimize the performance of the network, and to confirm the achievement of the KPIs. Furthermore, in the envisioned multi-site, multi-stakeholder scenarios, having a common monitoring system is even more critical for an efficient optimization and service provisioning. In this paper, we present a Monitoring architecture for the distribution and consumption of metrics and KPIs for 5G multi-site platforms, where different verticals from different stakeholders are implemented over a shared infrastructure. We also assess the performance of the implemented publish-subscribe paradigm, to confirm that it suits the requirements of these scenarios, and discuss how the architecture could be mapped to other 5G scenarios.
Demo: Assessing the need for 5G driven Edge and Fog solution for Digital Twin systems
(Association For Computing Machinery, 2020-09-25) Groshev, Milan; Guimarães, Carlos; European Commission
This demonstration presents the solution for a robotic Digital Twin system that integrates Fog computing to offload the robot control logic. This solution is then used to demonstrate the problems that Digital Twin system may face when performing teleoperation over an unreliable and delayed link.
5Growth: AI-driven 5G for Automation in Vertical Industries
(IEEE, 2020-06-15) Papagianni, Chrysa; Murillo, Pablo; Mangues-Bafalluy, Josep; Bermudez, Pedro; Barmpounakis, Sokratis; Vleeschauwer, Danny De; Brenes, Juan; Zeydan, Engin; Casetti, Claudio; Guimarães, Carlos; Garcia Saavedra, Andres; Corujo, Daniel; Pepe, Teresa; European Commission
Spurred by a growing demand for higher-quality mobile services in vertical industries, 5G is integrating a rich set of technologies, traditionally alien to the telco ecosystem, such as machine learning or cloud computing. Despite the initial steps taken in prior research projects in Europe and beyond, additional innovations are needed to support vertical use cases. This is the objective of the 5Growth project: automate vertical support through (i) a portal connecting verticals to 5G platforms (a.k.a. vertical slicer), a multi-domain service orchestrator and a resource management layer, (ii) closed-loop machine-learning-based Service Level Agreement (SLA) control, and (iii) end-to-end optimization. In this paper, we introduce a set of key 5Growth innovations supporting radio slicing, enhanced monitoring and analytics and integration of machine learning.
OKpi: All-KPI Network Slicing Through Efficient Resource Allocation
(IEEE, 2020-07-01) Martín Pérez, Jorge; Malandrino, Francesco; Chiasserini, C. F.; Bernardos Cano, Carlos Jesús; European Commission
Networks can now process data as well as transporting it; it follows that they can support multiple services, each requiring different key performance indicators (KPIs). Because of the former, it is critical to efficiently allocate network and computing resources to provide the required services, and, because of the latter, such decisions must jointly consider all KPIs targeted by a service. Accounting for newly introduced KPIs (e.g., availability and reliability) requires tailored models and solution strategies, and has been conspicuously neglected by existing works, which are instead built around traditional metrics like throughput and latency. We fill this gap by presenting a novel methodology and resource allocation scheme, named OKpi, which enables high-quality selection of radio points of access as well as VNF (Virtual Network Function) placement and data routing, with polynomial computational complexity. OKpi accounts for all relevant KPIs required by each service, and for any available resource from the fog to the cloud. We prove several important properties of OKpi and evaluate its performance in two real-world scenarios, finding it to closely match the optimum.
Experimenting with SRv6: a tunneling protocol supporting network slicing in 5G and beyond
(IEEE, 2020-09-30) Gramaglia, Marco; Sciancalepore, Vincenzo; Pérez, Ramón; Fernandez-Maestro, Francisco Javier; Serrano Yáñez-Mingot, Pablo; Banchs Roca, Albert; European Commission
With network slicing, operators can acquire and manage virtual instances of a mobile network, tailored to a given service, in this way maximizing flexibility whileincreasing the overall resource utilization. However, the currently used tunnelling protocol, i.e., GTP, might not be the most appropriate choice for the envisioned scenarios, given its unawareness of the underlay network. In this paper, we analyse the use of an alternative tunnelling protocol to transport user data, namely, Segment Routing IPv6 (SRv6). More specifically, we discuss its qualitative advantages, present a prototype implementation, and carry out an experimental comparison vs. GTP, confirming that it constitutes a valid alternative as tunnelling protocol
The case for serverless mobile networking
(IEEE, 2020-07-17) Gramaglia, Marco; Serrano Yáñez-Mingot, Pablo; Banchs Roca, Albert; García Avilés, Ginés; García-Saavedra, Andrés; Pérez, Ramón; European Commission
The softwarization of communication networks provides notable benefits, such as flexibility, improved resource efficiency, and commoditization. In exchange, softwarization requires an increased management overhead and the need to re-design network operation. While the mobile networking eco-system is currently adapting this new paradigm with other network-related aspects (e.g., network slicing), cloud computing already addressed such problems with the introduction of serverless architectures, also known as Function as a Service (FaaS). With this approach, the software is decomposed into its minimum building blocks, i.e., functions, maximizing scalability, resource efficiency, and flexibility. In this paper, we analyze the potential adoption of the FaaS paradigm by the mobile networking ecosystem, discussing the implicit advantages, the challenges to address, and some solutions to overcome them.
Constrained network slicing games: achieving service guarantees and network efficiency
(IEEE, 2020-08-04) Zheng, Jiaxiao; De Veciana, Gustavo; Banchs Roca, Albert; European Commission; Ministerio de Educación, Cultura y Deporte (España)
Network slicing is a key capability for next generation mobile networks. It enables one to cost effectively customize logical networks over a shared infrastructure. A critical component of network slicing is resource allocation, which needs to ensure that slices receive the resources needed to support their services while optimizing network efficiency. In this paper, we propose a novel approach to slice-based resource allocation named Guaranteed seRvice Efficient nETwork slicing (GREET). The underlying concept is to set up a constrained resource allocation game, where (i) slices unilaterally optimize their allocations to best meet their (dynamic) customer loads, while (ii) constraints are imposed to guarantee that, if they wish so, slices receive a pre-agreed share of the network resources. The resulting game is a variation of the well-known Fisher market, where slices are provided a budget to contend for network resources (as in a traditional Fisher market), but (unlike a Fisher market) prices are constrained for some resources to provide the desired guarantees. In this way, GREET combines the advantages of a share-based approach (high efficiency by flexible sharing) and reservation-based ones (which provide guarantees by assigning a fixed amount of resources). We characterize the Nash equilibrium, best response dynamics, and propose a practical slice strategy with provable convergence properties. Extensive simulations exhibit substantial improvements over network slicing state-of-the-art benchmarks.
Identifying common periodicities in mobile service demands with spectral analysis
(IEEE, 2020-09-20) Márquez Colás, María Cristina; Gramaglia, Marco; Fiore, Marco; Banchs Roca, Albert; Smoreda, Zbigniew; European Commission
In this paper, we investigate the existence and prevalence of comparable dynamics in the temporal fluctuations for the traffic demands generated by mobile applications.To this end, we hinge upon a spectral analysis framework, by computing Discrete Fourier Transforms of the typical demands for tens of popular mobile services observed in an operational metropolitan-scale network. We filter, cluster, and analyse hundreds of frequency components, and identify a substantial set of regular patterns that are common across most service demands. We also unveil how several mobile services defy classification, and have instead highly distinguishing temporal dynamics.
AZTEC: anticipatory capacity allocation for zero-touch network slicing
(IEEE, 2020-08-04) Bega, Dario; Gramaglia, Marco; Fiore, Marco; Banchs Roca, Albert; Costa-Pérez, Xavier; European Commission
The combination of network softwarization with network slicing enables the provisioning of very diverse services over the same network infrastructure. However, it also creates a complex environment where the orchestration of network resources cannot be guided by traditional, human-in-the-loop network management approaches. New solutions that perform these tasks automatically and in advance are needed, paving the way to zero-touch network slicing.In this paper, we propose AZTEC, a data-driven framework that effectively allocates capacity to individual slices by adopting an original multi-timescale forecasting model. Hinging on a combination of Deep Learning architectures and a traditional optimization algorithm, AZTEC anticipates resource assignments that minimize the comprehensive management costs induced by resource overprovisioning, instantiation and reconfiguration, as well as by denied traffic demands.Experiments with real-world mobile data traffic show that AZTEC dynamically adapts to traffic fluctuations, and largely outperforms state-of-the-art solutions for network resource orchestration.
5GEN: A tool to generate 5G infrastructure graphs
(IEEE, 2019-10-28) Martín Pérez, Jorge; Cominardi, Luca; Bernardos Cano, Carlos Jesús; Mourad, Alain; European Commission
Ongoing research on 5G is looking on software platforms to evaluate new developments on 5G networks. Some 5G hardware is now starting to be available, but it is scarce and very limited, which makes validation and performance evaluation of 5G quite challenging. Simulation is the tool of choice for most of the cases, but this requires creating large descriptor files representing a 5G network. This brings forward the need for tools that facilitate the generation of 5G networks' topologies. In this paper we present 5GEN, a tool that automatically creates graphs representing 5G networks. With 5GEN, a researcher can just define the number of resources, and 5GEN will generate the nodes and edges that interconnect them across the infrastructure. The tool has been successfully used to test several 5G network scenarios within the EU 5G-CORAL project.
Energy losses estimation tool for Low Voltage Smart grids
(AIM, 2019-06) Velasco Rodríguez, José Ángel; Amarís Duarte, Hortensia Elena; Alonso Martínez, Mónica; Casas, Marta; Ministerio de Economía y Competitividad (España)
The so-called 20-20-20 targets committed to by the European Union drives the need for a more efficient distribution network. The energy efficiency improvement required involves a 20% reduction of the energy consumption compared to the 1990s. For such cutback, Distribution Systems Operators are encouraged to develop the best strategies to identify and reduce power losses in their networks. This task becomes challenging in Low Voltage Distribution networks due to diversity in the feeder's topology configuration, load distribution and the presence of renewable-based distributed generation. In this paper, a clustering-based methodology is proposed as an energy losses tool to support the energy efficiency decision-making process. A feeder's clustering process using the K-means algorithm is carried out upon a customised network characteristics set that was previously reduced to two coordinates by applying Principal Component Analysis. The relationship between power losses and the net energy imported under the different scenarios is obtained for each feeder class identified. The data and network used in this process correspond to the roll-out deployed at the Spanish Smart Grid Demonstration Project (OSIRIS)
Overbooking Network Slices End-to-End: Implementation and Demonstration
(Association for Computing Machinery, 2018-08) Zanzi, Lanfranco; Salvat, Josep Xavier; Sciancalepore, Vincenzo; García-Saavedra, Andrés; Costa-Pérez, Xavier
The novel network slicing paradigm allows service providers to open their infrastructure to new business players such as vertical industries. In this demo, we showcase the benefits of our proposed end-to-end network slicing orchestration solution that blends together i) an admission control engine able to handle heterogeneous network slice requests, ii) a resource allocation solution across multiple network domains: radio access, edge, transport and core networks and iii) a monitoring, forecasting and dynamic configuration solution that maximizes the statistical multiplexing of network slices resources. Our orchestration solution is operated through a dashboard that allows requesting network slices on-demand, monitors their performance once deployed and displays the achieved multiplexing gain through overbooking.

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