Artículos (Ingeniería Telemática)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11387

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Hybrid Fault-Space Restructuring for Machine Learning-Based Fault Diagnosis in Power Electronic Converters
(Multidisciplinary Digital Publishing Institute (MDPI), 2026-07) García-Campos, José Manuel; Márquez Alcaide, Abraham; Letrado Castellanos, Alejandro; Portillo Guisado, Ramón Carlos; León Galván, José Ignacio; Ingeniería Electrónica; Ingeniería Telemática; Ministerio de Ciencia e Innovación (MICIN). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Hacienda y Función Publica; Junta de Andalucía; Shanghai Partner Research Program
Fault diagnosis in power electronic systems is challenging when fault categories geometrically overlap within the measurement space, limiting class separability and introducing classification ambiguity. This work proposes an edge-oriented hybrid fault-space restructuring methodology that utilizes UMAP-based embeddings and hierarchical clustering to group overlapping fault conditions into robust hybrid representations. Subsequently, supervised machine learning models execute the final classification over this optimized space. Validation was conducted using a large-scale synthetic dataset generated via real-time hardware-in-the-loop (HIL) simulation, evaluating electrical measurements from three-dimensional RMS values to 60-dimensional instantaneous waveforms. Tested with Decision Tree and Random Forest algorithms, the restructuring strategy significantly improves robustness under geometric ambiguity compared to conventional classification without space restructuring. Specifically, low-dimensional measurements achieved F1-score improvements of approximately 72% and 46% for the Decision Tree and Random Forest algorithms, respectively, while high-dimensional measurement configurations still exhibited significant improvements of 36% and 52%. Consequently, these results confirm that the combined restructuring and classification pipeline is highly effective across the analyzed measurement dimensionalities, establishing a dependable cluster-based diagnostic strategy that enhances classification robustness while accepting a trade-off in individual fault-isolation granularity. Finally, hardware deployment experiments on a Raspberry Pi 4 platform demonstrated the feasibility of executing the trained classifiers for real-time inference under constrained computational environments. The experimental evaluation validated real-time execution capabilities, achieving sub-millisecond inference latencies (as low as 0.32 ms), a memory footprint under 0.14 MB, and processing rates exceeding 2600 inferences per second using lightweight Decision Tree classifiers. Ultimately, these findings indicate that the proposed strategy improves fault detection across the evaluated measurement configurations while ensuring a highly viable execution on resource-constrained devices once the classifiers are trained.
On Gamification in the Context of Education: A Systematic Review and Evaluation Framework
(Wiley, 2026-05) Muñoz Calle, Francisco Javier; Candilejo Egea, José Manuel; Fernández Jiménez, Francisco José; Muñoz Calle, Jesús Manuel; Ingeniería Telemática; Red Educativa Digital Descartes
The application of gamification techniques in education is becoming increasingly common across different educational stages and disciplines. However, the widespread acceptance of their benefits leads to their implementation without verifying whether these benefits occur, what they are, and to what extent. This work addresses the need for a rigorous methodology to evaluate gamified experiences and aims to facilitate objective comparison between them. A robust statistical evaluation methodology, termed Gamification Impact Evaluation based on the Analytic Hierarchy Process (GIE-AHP), is proposed and implemented. GIE-AHP weighs multiple relevant criteria and sub-criteria in an adaptable and reproducible manner. This work also presents a systematic review of previous empirical studies on gamified education, identifying success parameters, techniques employed, and methodological shortcomings, which serve as the basis for defining the GIE-AHP criteria. Finally, the GIE-AHP approach is validated empirically through the development and analysis of the Project Pony, a set of five real-world experiences carried out in diverse educational settings. The results demonstrate the utility of the GIE-AHP methodology for objectively quantifying the impact of experiences in terms of their academic, motivational, and behavioral dimensions, as well as design aspects. Therefore, this represents a substantial advancement in the direction of achieving uniformity in educational gamification evaluation.
Fog Computing and Graph-Based Databases for Remote Health Monitoring in IoMT Settings
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-12) Yousif, K.A.; Calvillo Arbizu, Jorge; Lara Romero, Agustín Walabonso; Ingeniería Telemática
Remote patient monitoring is a promising and transformative pillar of healthcare. However, deploying such systems at a scale—across thousands of patients and Internet of Medical Things (IoMT) devices—demands robust, low-latency, and scalable storage systems. This research examines the application of Fog Computing for remote patient monitoring in IoMT settings, where a large volume of data, low latency, and secure management of confidential healthcare information are essential. We propose a four-layer IoMT–Fog–Cloud architecture in which Fog nodes, equipped with graph-based databases (Neo4j), conduct local processing, filtering, and integration of heterogeneous health data before transmitting it to cloud servers. To assess the viability of our approach, we implemented a containerised Fog node and simulated multiple patient-device networks using a real-world dataset. System performance was evaluated using 11 scenarios with varying numbers of devices and data transmission frequencies. Performance metrics include CPU load, memory footprint, and query latency. The results demonstrate that Neo4j can efficiently ingest and query millions of health observations with an acceptable latency of less than 500 ms, even in extreme scenarios involving more than 12,000 devices transmitting data every 50 ms. The resource consumption remained well below the critical thresholds, highlighting the suitability of the proposed approach for Fog nodes. Combining Fog computing and Neo4j is a novel approach that meets the latency and real-time data ingestion requirements of IoMT environments. Therefore, it is suitable for supporting delay-sensitive monitoring programmes, where rapid detection of anomalies is critical (e.g., a prompt response to cardiac emergencies or early detection of respiratory deterioration in patients with chronic obstructive pulmonary disease), even at a large scale.
Anomaly-based Intrusion Detection System for smart lighting
(Elsevier, 2024-12) Lara Romero, Agustín Walabonso; Estepa Alonso, Antonio José; Estepa Alonso, Rafael María; Díaz Verdejo, Jesús; Mayor Gallego, Vicente Jesús; Ingeniería Telemática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España
Smart Lighting Systems (SLS) are essential to smart cities, offering enhanced energy efficiency and public safety. However, they are susceptible to security threats, potentially leading to safety risks and service disruptions, making the protection of this infrastructure critical. This paper presents an anomaly-based Intrusion Detection System (IDS) designed for a real-world operational SLS. As commercial deployments vary in components, protocols, and functionalities, IDSs must be tailored to the specific characteristics of each deployment to perform effectively. Our anomaly-based IDS has been defined based on the properties of the available data and the types of attacks we aim to detect, offering both explainability and low complexity. The proposed system identifies anomalies in seven features of network traffic and in the telemetry data received at the central control (O&M) server. For the latter, we designed three customized detectors to identify abnormal data points, persistent deviations in street lamp power consumption, and abnormal power value based on the time of day. Validation with real-world data and simulated attacks demonstrates the effectiveness of our approach. Network attacks (e.g., DoS, scanning) were detected by at least one of the seven flow-related anomaly detectors, while simulated data poisoning attacks and operational technology (OT) issues were detected with nearly 90% accuracy. The datasets used in this work are publicly available and may serve as reference for the design of future IDSs. While our detectors were designed specifically for our dataset, the variables examined and vulnerabilities addressed are common in most commercial SLSs.
Controlled Generation of Synthetic Spanish Texts: A Dataset Using LLMs with and Without Contextual Retrieval
(Multidisciplinary Digital Publishing Institute (MDPI), 2026-02) García-Campos, José Manuel; Lara Romero, Agustín Walabonso; Mayor Gallego, Vicente Jesús; Calvillo Arbizu, Jorge; Ingeniería Telemática; TIC203: Ingeniería Biomédica
The increasing ability of Large Language Models (LLMs) to generate fluent and coherent text has heightened the need for resources to analyze and detect synthetic content, particularly in Spanish, where the scarcity of datasets hinders the development of reliable detection systems. This work presents a Spanish-language dataset of 18,236 synthetic news descriptions generated from real journalistic headlines using a fully reproducible, open-source pipeline. The methodology used to produce the dataset includes both a Retrieval Augmented Generation (RAG) approach, which incorporates contextual information from recent news descriptions, and a NO-RAG approach, which relies solely on the headline. Texts were generated with the instruction-tuned Mistral 7B Instruct model, systematically varying temperature to explore the effect of generation parameters. The dataset includes detailed metadata linking each synthetic description to its source headline, generation settings, and, when applicable, retrieved contextual content. By combining contextual grounding, controlled parameter variation, and source-level traceability, this dataset provides a reproducible and richly annotated resource that supports research in Spanish synthetic text and evaluation of LLM-based generation.
A Scalable Microservices Architecture for Condition Monitoring and State-of-Health Tracking in Power Conversion Systems
(Multidisciplinary Digital Publishing Institute (MDPI), 2026-02) García-Campos, José Manuel; Márquez Alcaide, Abraham; Letrado Castellanos, Alejandro; Portillo Guisado, Ramón Carlos; León Galván, José Ignacio; Ingeniería Telemática; Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; European Union (UE); Shanghai Partner Research Program
The role of power converters in modern electrical infrastructure (such as electric vehicle charging stations, battery energy storage systems and photovoltaic energy systems) has become critical. Given the high reliability required by these converters, continuous condition monitoring for predictive maintenance is mandatory. Traditional SCADA and HMI systems often face scalability bottlenecks and lack the flexibility in data aggregation and storage scalability required for long-term predictive maintenance. This paper proposes a scalable, containerized microservices-based architecture for degradation tracking and State-of-Health (SoH) monitoring in power conversion systems. The architecture features a decoupled four-layer structure, utilizing dedicated UDP servers for low-latency data ingestion, RabbitMQ (AMQP) for robust message routing, and a NoSQL (MongoDB) storage layer with a FastAPI interface. The proposed system was validated using a Hardware-in-the-Loop (HiL) setup with a Typhoon HIL606 simulator monitoring an Active Neutral Point Clamped (ANPC) power converter. Experimental stress tests demonstrated a Packet Delivery Ratio (PDR) of 1.0 at ingestion rates up to 100 messages per second (msgs/s) per node. The system exhibits transmission and processing overheads consistently below 5 ms, ensuring timely data availability for tracking thermal dynamics and parametric aging trends. This operational performance significantly exceeds the nominal requirement of 2 msgs/s for condition monitoring, ensuring robust data integrity. Finally, this modular approach provides the horizontal scalability necessary for Industry 4.0 integration, offering a high-performance framework for long-term health monitoring in modern power electronics.
Experiences applying RM-ODP principles and techniques to intelligent transportation system architectures
(Elsevier, 2013-03) Román Martínez, Isabel; Madinabeitia Luque, Germán; Jiménez, L.; Molina, G.A.; Ternero Muñiz, Juan Antonio; Ingeniería Telemática
This paper shows the early experiences transferring architectural knowledge from Academic to Industry within an R + D + I project. This is done through the design and development of an Intelligent Transportation System (ITS) Architecture following SOA and RM-ODP principles, to facilitate openness, reusability, scalability and interoperability. Rationale selection of standards, technologies and platforms, considering system's requirements (real time, cost ellipsis) has been done. An iterative agile development process, with incremental stages from design to final prototype, has been used. Early outcomes are centered in two services; multimedia flow management and notification. They have been developed using CORBA and are embedded in system's devices.
Development and Validation in Porcine and Human Models of a Bioimpedance Spectroscopy System for the Objective Assessment of Kidney Graft Viability
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Naranjo Hernández, David; Reina Tosina, Luis Javier; Roa Romero, Laura María; Barbarov-Rostán, Gerardo; Calvillo Arbizu, Jorge; Talaminos Barroso, Alejandro; Pérez Valdivia, Miguel Ángel; Medina López, Rafael; Teoría de la Señal y Comunicaciones; Ingeniería Telemática; Medicina; Cirugía; Fundación Mutua Madrileña; Junta de Andalucía
This work presents an innovative bioimpedance spectroscopy device, developed as a support tool for decision-making during the evaluation of kidney viability for renal transplantation. Given the increasing demand for organs and the need to optimize donation criteria, the precise and objective assessment of renal graft functionality has become crucial. The device, based on a modular design and adapted to the surgical environment, uses a novel Cole model with a frequency-dependent membrane capacitance, which improves measurement accuracy and repeatability compared to conventional models. Adapting the device for operating room usege involved overcoming significant challenges, such as the need for sterilization and a visual, tactile and acoustic user interface that facilitates device usability. Optimizing the sensing stage has minimized the influence of measurement artifacts, which is crucial for obtaining accurate and representative measurements of renal tissue bioelectrical properties. In addition, a rigorous electrode sterilization protocol was designed, ensuring asepsis during the procedure. The results of tests on porcine renal models demonstrated the device’s ability to monitor pathophysiological changes associated with renal ischemia, with a notable improvement against measurement repeatability.
Building a large, realistic and labeled HTTP URI dataset for anomaly-based intrusion detection systems: Biblio-US17
(Springer, 2025) Díaz Verdejo, Jesús; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Muñoz Calle, Francisco Javier; Madinabeitia Luque, Germán; Ingeniería Telemática; Ministerio de Ciencia e Innovación (MICIN). España; TIC154: Departamento de Ingeniería Telemática
This paper introduces Biblio-US17, a labeled dataset collected over 6 months from the log fles of a popular public website at the University of Seville. It contains 47 million records, each including the method, uniform resource identifer (URI) and associated response code and size of every request received by the web server. Records have been classifed as either normal or attack using a comprehensive semi-automated process, which involved signature-based detection, assisted inspection of URIs vocabulary, and substantial expert manual supervision. Unlike comparable datasets, this one ofers a genuine real-world perspective on the normal operation of an active website, along with an unbiased proportion of actual attacks (i.e., non-synthetic). This makes it ideal for evaluating and comparing anomalybased approaches in a realistic environment. Its extensive size and duration also make it valuable for addressing challenges like data shift and insufcient training. This paper describes the collection and labeling processes, dataset structure, and most relevant properties. We also include an example of an application for assessing the performance of a simple anomaly detector. Biblio-US17, now available to the scientifc community, can also be used to model the URIs used by current web servers.
A Flexible Multilevel System for Mitre ATT&CK Model-driven Alerts and Events Correlation in Cyberattacks Detection
(Journal of Universal Computer Science, 2024) Muñoz Calle, Francisco Javier; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Díaz Verdejo, Jesús; Castillo Fernández, Elvira; Madinabeitia Luque, Germán; Ingeniería Telemática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; TIC154: Departamento de Ingeniería Telemática
Network monitoring systems can struggle to detect the full sequence of actions in a multi-step cyber attack, frequently resulting in multiple alerts (some of which are false positive (FP)) and missed actions. The challenge of easing the job of security analysts by triggering a single and accurate alert per attack requires developing and evaluating advanced event correlation techniques and models that have the potential to devise relationships between the different observed events/alerts. This work introduces a flexible architecture designed for hierarchical and iterative correlation of alerts and events. Its key feature is the sequential correlation of operations targeting specific attack episodes or aspects. This architecture utilizes IDS alerts or similar cybersecurity sensors, storing events and alerts in a non-relational database. Modules designed for knowledge creation then query these stored items to generate meta-alerts, also stored in the database. This approach facilitates creating a more refined knowledge that can be built on top of existing one by creating specialized modules. For illustrative purposes, we make a case study where we use this architectural approach to explore the feasibility of monitoring the progress of attacks of increased complexity by increasing the levels of the hyperalerts defined, including a case of a multi-step attack that adheres to the ATT&CK model. Although the mapping between the observations and the model components (i.e., techniques and tactics) is challenging, we could fully monitor the progress of two attacks and up to 5 out of 6 steps of the most complex attack by building up to three specialized modules. Despite some limitations due to the sensors and attack scenarios tested, the results indicate the architecture’s potential for enhancing the detection of complex cyber attacks, offering a promising direction for future cybersecurity research.
A methodology for conducting efficient sanitization of HTTP training datasets
(Elsevier, 2020-08) Díaz Verdejo, Jesús; Estepa Alonso, Antonio José; Estepa Alonso, Rafael María; Madinabeitia Luque, Germán; Muñoz Calle, Francisco Javier; Ingeniería Telemática; Cooperación Tecnológica de Andalucía; Universidad de Sevilla; TIC154: Departamento de Ingeniería Telemática
The performance of anomaly-based intrusion detection systems depends on the quality of the datasets used to form normal activity profiles. Suitable datasets should include high volumes of real-life data free from attack instances. On account of this requirement, obtaining quality datasets from collected data requires a process of data sanitization that may be prohibitive if done manually, or uncertain if fully automated. In this work, we propose a sanitization approach for obtaining datasets from HTTP traces suited for training, testing, or validating anomaly-based attack detectors. Our methodology has two sequential phases. In the first phase, we clean known attacks from data using a pattern-based approach that relies on tools that detect URI-based known attacks. In the second phase, we complement the result of the first phase by conducting assisted manual labeling systematically and efficiently, setting the focus of expert examination not on the raw data (which would be millions of URIs), but on the set of words that compose the URIs. This dramatically downsizes the volume of data that requires expert discernment, making manual sanitization of large datasets feasible. We have applied our method to sanitize a trace that includes 45 million requests received by the library web server of the University of Seville. We were able to generate clean datasets in less than 84 h with only 33 h of manual supervision. We have also applied our method to some public benchmark datasets, confirming that attacks unnoticed by signature-based detectors can be discovered in a reduced time span.
Use of TDM pseudo-wires for an efficient NGN emulation of ISDN multi-channel circuit-mode bearer services
(River Publishers ; Rinton Press, 2014-03) Muñoz Calle, Francisco Javier; Sierra Collado, Antonio Jesús; Vozmediano Torres, Juan Manuel; Ingeniería Telemática
The specifications of the Next Generation Networks (NGN) agree on the need for migration mechanisms that enable the replacement of traditional networks, highlighting the ISDN networks. This requirement has a notable impact on NGN in terms of network design. Recent solutions proposed by ITU-T and ETSI for ISDN migration only include support for a subset of current ISDN services, not covering in detail the multi-channel circuit-mode bearer services. This paper examines the use of TDM pseudowires for NGN emulation of ISDN multi-channel calls between ISDN terminals, proposing new payload types.
Computing Labs on Virtual Environments: A Flexible, Portable, and Multidisciplinary Model
(IEEE, 2016-11) Muñoz Calle, Francisco Javier; Fernández Jiménez, Francisco José; Ariza Gómez, María Teresa; Sierra Collado, Antonio Jesús; Vozmediano Torres, Juan Manuel; Ingeniería Telemática
Computer-aided teaching of practical subjects in engineering education poses new challenges. Computers have to be configured to support the particular requirements of each subject. Virtual environments allow the building of a virtual machine (VM) tailored to the requirements of each subject, allowing flexible, versatile, and low-cost laboratory configurations. However, the use of multiple VM at a shared computing facility poses new problems on the lab sessions, both technical and performance related. To solve these challenges, we have developed the VM on-demand tool. This tool automates the adaptation of each VM to the environment in which it is deployed. As a result, the creation of computer-aided engineering laboratories on a shared computing facility using VM is possible and profitable.
Emulation of ISDN Multi-channel Circuit-mode Bearer Services in Next Generation Networks by TDM Pseudo-Wires
(Institute of Electrical and Electronics Engineers (IEEE), 2012-12) Muñoz Calle, Francisco Javier; Sierra Collado, Antonio Jesús; Vozmediano Torres, Juan Manuel; Ingeniería Telemática
The specifications of the Next Generation Networks (NGN) agree on the need for migration mechanisms that enable the replacement of traditional networks, highlighting the ISDN networks. This requirement has a notable impact on NGN in terms of network design. Recent solutions proposed by ITU-T and ETSI for ISDN migration only include support for a subset of current ISDN services, not covering in detail the multi-channel circuit-mode bearer services. This paper examines the use of TDM pseudowires for NGN emulation of ISDN multi-channel calls between ISDN terminals, proposing new payload types.
A survey on unmanned aerial and aquatic vehicle multi-hop networks: Wireless communications, evaluation tools and applications
(Elsevier, 2018-04) Sánchez García, Jesús; García-Campos, José Manuel; Arzamendia, Mario; Gutiérrez Reina, Daniel; Toral, S. L.; Gregor, Derlis O.; Ingeniería Telemática; Ingeniería Electrónica
Unmanned aerial and aquatic vehicle networks have attracted the attention of the wireless communication research community in the last decade. The low manufacturing costs for developing small unmanned vehicles and the notable developments on wireless communication technologies have made possible the design of cooperative applications involving multiple unmanned aerial and aquatic vehicles. However, the design of wireless networks, which include very dynamic and complex entities like unmanned vehicles, poses many challenges. Fortunately, unmanned aerial vehicle networks applications usually resemble those of unmanned aquatic vehicle networks such as military missions, or environmental monitoring among others. With the exception of the obvious differences in the lower layers of the wireless communications protocols, valid approaches used in the aerial medium could be easily adapted to the aquatic medium. This survey presents together the main features to take into account for designing unmanned aerial and aquatic vehicle networks with the aim to help the reader to transfer valid approaches and techniques between aerial and aquatic applications. We survey the results of more than 100 references on this topic published in international conferences and journals, and we also include the results of several bibliometric analyses in order to better present the status of the art and research directions on this scientific area.
Minimizing energy consumption in 802.15.4 IoT devices with multilevel xRPL (MxRPL)
(Elsevier, 2023-12) Ternero Muñiz, Juan Antonio; Mayor Gallego, Vicente Jesús; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Madinabeitia Luque, Germán; Ingeniería Telemática; TIC154: Departamento de Ingeniería Telemática
IoT devices using IEEE 802.15.4 radio links may offer adaptable transmit power. But, since transmit power determines coverage, the problem of choosing the optimal tx power for each node is intertwined with the routing problem. We present a new cross-layer routing approach for reducing energy consumption in IEEE 802.15.4 IoT devices with adjustable radio power level termed multilevel cross-layer RPL (MxRPL). In our scheme, each node sets its tx power level according to the RPL parent chosen in the path with the lowest additive product of ETX and nodes’ tx power. We also propose a new probing mechanism that maintains fresh link statistics for each neighbor and power level restraining the associated control messages. We have implemented our approach in Cooja’s Z1 mote and simulated a network with 15 nodes in areas of different size. The results show that MxRPL achieves energy savings in the radio of up to 34% in reception and 20% in transmission compared to a simpler cross-layer binary approach previously published by the authors (i.e., each node chooses either its maximum or minimum tx power level). Energy savings are even greater compared to default RPL (up to 40% in reception and 26% in transmission). This is mostly attributable to the generation of less control messages and a more efficient use of tx power. Our scheme exhibits better results in medium and large size scenarios (e.g., 25 m 25 m, 42 m2 /node), whereas a simpler binary approach is slightly more advantageous in small and dense scenarios.
Supporting VoIP communication in IEEE 802.11ax networks: A new admission control and scheduling resource allocation scheme
(Elsevier, 2024-08) Estepa Alonso, Rafael María; Davis, Mark; Mayor Gallego, Vicente Jesús; Estepa Alonso, Antonio José; Ingeniería Telemática; Universidad de Sevilla; TIC154: Departamento de Ingeniería Telemática
The current IEEE 802.11ax standard enhances Wi-Fi networks with a series of new features, such as multi-user (MU) transmission, an Orthogonal Frequency Division Multiple Access (OFDMA) scheme and the ability to multiplex traffic from different access categories (ACs). These features can be utilized to enhance the QoS support for VoIP traffic and optimize the usage of IEEE 802.11ax network resources. This work proposes a new scheme to multiplex VoIP calls in IEEE 802.11ax MU frames and a new scheduler and resource allocation algorithm specifically designed for VoIP data traffic. Our scheduler allocates VoIP packets requiring longer transmission times into the same frame(s), minimizing the channel air-time assigned to VoIP transmission. In addition, unused radio resources in the MU frame are leveraged to transmit best-effort packets along with VoIP packets. For completeness, we also define a call admission control (CAC) algorithm that anticipates channel saturation conditions to ensure VoIP users can maintain a guaranteed level of QoS. Based on simulation results, our scheme is more efficient in reducing channel utilization than other schedulers such as multi-user roundrobin (RR) (implemented by ns-3) or single-user FIFO. For example, for 30 VoIP stations using the G.711 codec under mixed channel conditions, our scheme reduces by 30% the air-time required to transmit VoIP packets. When coupled with the ability to also send best-effort packets along with VoIP packets, this translates into a higher throughput (i.e. 10 Mbit/s vs 4 Mbit/s) and more simultaneous VoIP users with guaranteed QoS (up to 46 VoIP users vs 26 and 28 users for the multi-user RR and single-user FIFO scheduling algorithms, respectively).
Smart home anomaly-based IDS: architecture proposal and case study
(Elsevier, 2023) Lara Romero, Agustín Walabonso; Mayor Gallego, Vicente Jesús; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Díaz Verdejo, Jesús; Ingeniería Telemática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Fondo Europeo de Desarrollo Regional (FEDER); Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Junta de Andalucía; TIC154: Departamento de Ingeniería Telemática
The complexity and diversity of the technologies involved in the Internet of Things (IoT) challenge the generalization of security solutions based on anomaly detection, which should fit the particularities of each context and deployment and allow for performance comparison. In this work, we provide a flexible architecture based on building blocks suited for detecting anomalies in the network traffic and the application-layer data exchanged by IoT devices in the context of Smart Home. Following this architecture, we have defined a particular Intrusion Detector System (IDS) for a case study that uses a public dataset with the electrical consumption of 21 home devices over one year. In particular, we have defined ten Indicators of Compromise (IoC) to detect network attacks and two anomaly detectors to detect false command or data injection attacks. We have also included a signature-based IDS (Snort) to extend the detection range to known attacks. We have reproduced eight network attacks (e.g., DoS, scanning) and four False Command or Data Injection attacks to test our IDS performance. The results show that all attacks were successfully detected by our IoCs and anomaly detectors with a false positive rate lower than 0.3%. Signature detection was able to detect only 4 out of 12 attacks. Our architecture and the IDS developed can be a reference for developing future IDS suited to different contexts or use cases. Given that we use a public dataset, our contribution can also serve as a baseline for comparison with new techniques that improve detection performance.
Blockchain-Based Service-Oriented Architecture for Consent Management, Access Control, and Auditing
(Institute of Electrical and Electronics Engineers Inc., 2023) Román Martínez, Isabel; Calvillo Arbizu, Jorge; Mayor Gallego, Vicente Jesús; Madinabeitia Luque, Germán; Estepa Alonso, Antonio José; Estepa Alonso, Rafael María; Ingeniería Telemática; Ministerio de Ciencia e Innovación; TIC154: Departamento de Ingeniería Telemática
Continuity of care requires the exchange of health information among organizations and care teams. The EU General Data Protection Regulation (GDPR) establishes that subject of care should give explicit consent to the treatment of her personal data, and organizations must obey the individual’s will. Nevertheless, few solutions focus on guaranteeing the proper execution of consents. We propose a serviceoriented architecture, backed by blockchain technology, that enables: (1) tamper-proof and immutable storage of subject of care consents; (2) a fine-grained access control for protecting health data according to consents; and (3) auditing tasks for supervisory authorities (or subjects of care themselves) to assess that healthcare organizations comply with GDPR and granted consents. Standards for health information exchange and access control are adopted to guarantee interoperability. Access control events and the subject of care consents are maintained on a blockchain, providing a trusted collaboration between organizations, supervisory authorities, and individuals. A prototype of the architecture has been implemented as a proof of concept to evaluate the performance of critical components. The application of subject of care consent to control the treatment of personal health data in federated and distributed environments is a pressing concern. The experimental results show that blockchain can effectively support sharing consent and audit events among healthcare organizations, supervisory authorities, and individuals.
CO-CAC: A new approach to Call Admission Control for VoIP in 5G/WiFi UAV-based relay networks
(Elsevier, 2023-01) Mayor Gallego, Vicente Jesús; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Ingeniería Telemática; TIC154: Ingeniería Telemática
Voice over IP (VoIP) requires a Call Admission Control (CAC) mechanism in WiFi networks to preserve VoIP packet flows from excessive network delay or packet loss. Ideally, this mechanism should be integrated with the operational scenario, guarantee the quality of service of active calls, and maximize the number of concurrent calls. This paper presents a novel CAC scheme for VoIP in the context of a WiFi access network deployed with Unmanned Aerial Vehicles (UAVs) that relay to a backhaul 5G network. Our system, named Codec-Optimization CAC (CO-CAC), is integrated into each drone. It intercepts VoIP call control messages and decides on the admission of every new call based on a prediction of the WiFi network’s congestion level and the minimum quality of service desired for VoIP calls. To maximize the number of concurrent calls, CO-CAC proactively optimizes the codec settings of active calls by exchanging signaling with VoIP users. We have simulated CO-CAC in a 50 m 50 m scenario with four UAVs providing VoIP service to up to 200 ground users with IEEE 802.11ac WiFi terminals. Our results show that without CAC, the number of calls that did not meet a minimum quality level during the simulation was 10% and 90%, for 50 and 200 users, respectively. However, when CO-CAC was in place, all calls achieved minimum quality for up to 90 users without rejecting any call. For 200 users, only 25% of call attempts were rejected by the admission control scheme. These results were narrowly worse when the ground users moved randomly in the scenario.

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