Resultados de investigación

This repository contains a publicly available ATT&CK-oriented network attack dataset composed of manually generated and labeled PCAPNG captures associated with MITRE ATT&CK Enterprise techniques and sub-techniques observable from network traffic. The dataset was generated under controlled laboratory conditions using real offensive tools, vulnerable services, protocol-compliant implementations, and manually supervised attack execution procedures. The repository includes original PCAPNG captures, manually labeled flow annotations, attack metadata, Snort configurations and rule sets, and the pruning evaluation results employed throughout the experimental study. The objective of the dataset is to provide a realistic and reproducible benchmark for evaluating intrusion detection systems, ATT&CK-oriented monitoring approaches, traffic analysis methodologies, flow-based detection techniques, and rule pruning strategies.

Documento de transferencia que integra la Memoria Técnica y Visual de la investigación "Ectopías Asémicas", presentada como ponencia y exhibición artística en el III Congreso Internacional GIPAFCoCo (Imágenes y Escrituras Generativas en las Prácticas Artísticas Contemporáneas) y la muestra "Latencias". El documento incluye: Certificación Oficial con Código Seguro de Verificación (CSV) emitida por la Facultad de Bellas Artes de la Universidad Complutense de Madrid (UCM). Planteamiento teórico-metodológico sobre la hibridación de alfabetos en peligro de desaparición y sistemas generativos. Especificaciones técnicas de instalación para entornos físicos y virtuales (Metaverso), incluyendo esquemas de espacialización sonora y visual. Registro de resultados de la muestra "Latencias", respaldada por el Vicerrectorado de Investigación y Transferencia de la UCM., ta aportación recoge la memoria técnica y visual de la ponencia y exhibición de resultados de investigación presentadas en el marco del III Congreso Internacional GIPAFCoCo y la muestra "Latencias", celebrados en la Facultad de Bellas Artes de la Universidad Complutense de Madrid (octubre, 2025). Bajo el título "Ectopías Asémicas", la investigación explora la convergencia entre los sistemas de escritura en peligro de desaparición (como los alfabetos Hanunoo, Sundanés y Buhid) y los procesos de creación algorítmica en entornos de metaverso. El proyecto propone una metodología de "investigación-creación" donde la tecnología actúa como un puente de preservación cultural y experimentación estética. La memoria detalla el desarrollo de figuras humanas de formato phygital (hibridación físico-digital), el uso de iteraciones sobre símbolos Unicode para generar arquitecturas virtuales y la implementación de sistemas de espacialización sonora sinestésica. El documento incluye el certificado oficial de participación con código seguro de verificación (CSV), el programa del congreso avalado por el Vicerrectorado de Investigación y Transferencia de la UCM, y un dossier técnico con esquemas de instalación y registros visuales de las obras en espacios virtuales y físicos. Esta obra representa un hito en la transferencia de conocimiento desde la práctica artística contemporánea hacia las humanidades digitales y la industria de contenidos inmersivos, Vicerrectorado de Investigación y Transferencia de la Universidad Complutense de Madrid (UCM).

Supplementary dataset associated with the article “Bioaccessibility of Metal(loid)s From Anthropogenic Contamination in Dry Riverbed Sediments in the Cartagena–La Unión Mining District (Murcia, SE Spain): Implications for Human Health Risk Assessment”. The dataset contains contamination factor (CF), pollution load index (PLI), correlation analyses, hazard quotients (HQ), and carcinogenic risk (CR) results for 52 sediment samples collected from three dry riverbeds affected by historical mining activity in the Cartagena–La Unión Mining District: El Beal (20 samples), Las Matildes (13 samples), and Ponce (19 samples). The dataset includes results based on total metal(loid) concentrations and gastric-phase bioaccessible concentrations determined using the SBRC method., Proyecto PID2019-110311RB-C22.

The files named medidas4_4_4__2025-02-12-xxxxxx contains the channel frequency response, with dimensions of 4×4×4×9285×14 for the D-band and 4×4×4×8092×14 for the W-band. The first dimension corresponds to the receiver uniform linear array (ULA). The second and third dimensions (4×4) represent the transmitter uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (9285 for the D-band and 8092 for the W-band). The fifth dimension (14) corresponds to the different positions at which the transmitting URA was placed. D band For the D-band, the relationship between the measurement files and the transmitter positions is defined as follows: medidas4_4_4__2025-02-12-191858 Tx position 1 medidas4_4_4__2025-02-15-175116 Tx position 2 medidas4_4_4__2025-02-05-190501 Tx position 3 medidas4_4_4__2025-02-06-230621 Tx position 4 medidas4_4_4__2025-02-08-170519 Tx position 5 medidas4_4_4__2025-01-30-131834 Tx position 6 medidas4_4_4__2025-01-31-193904 Tx position 7 medidas4_4_4__2025-02-04-145441 Tx position 8 medidas4_4_4__2025-01-22-184320 Tx position 9 medidas4_4_4__2025-01-24-132048 Tx position 10 medidas4_4_4_16384_2025-01-28-143716 Tx position p11 medidas4_4_4__2025-01-25-185634 Tx position p12 medidas4_4_4__2025-01-18-152908 Tx position p13 medidas4_4_4__2025-01-21-142107 Tx position p14 The MATLAB script D_band_full computes the K-factor, coherence bandwidth, frequency-response magnitude, RMS delay spread, and the parameters of the FI and CI models. The MATLAB script D_band_models estimates the parameters of the FI, CI, CIF, and ABG path-loss models. W band For the W-band the relationship between the measurement file and the transmitter positions is defined as follows: medidas4_4_4_8092_2025-07-03-190657 Tx position 1 medidas4_4_4_8092_2025-07-03-170215 Tx position 2 medidas4_4_4_8092_2025-07-03-144335 Tx position 3 medidas4_4_4_8092_2025-07-03-122031 Tx position 4 medidas4_4_4_8092_2025-07-02-181219 Tx position 5 medidas4_4_4_8092_2025-07-01-123100 Tx position 6 medidas4_4_4_8092_2025-07-01-152250 TX position 7 medidas4_4_4_8092_2025-07-02-154639 TX position 8 medidas4_4_4_8092_2025-06-30-183855 TX position 9 medidas4_4_4_8092_2025-06-30-160643 TX position 10 medidas4_4_4_8092_2025-06-30-205212 TX position 11 medidas4_4_4_8192_2025-06-26-204518 TX position 12 medidas4_4_4_8192_2025-06-27-133916 TX position 13 medidas4_4_4_8092_2025-06-30-113953 TX position 14 The MATLAB script W_band_full computes the K-factor, coherence bandwidth, frequency-response magnitude, RMS delay spread, and the parameters of the FI and CI models. The MATLAB script W_band_models estimates the parameters of the FI, CI, CIF, and ABG path-loss models. The MATLAB script D_W_full computes the K-factor CDF and the power delay profile (PDP) for both frequency bands. The function calcula_RMS computes the RMS DS The function coherence_bandwidth_frequency computes the coherence bandwith, This dataset is composed of a set of measurements and the code to analyze the measurements. The files named medidas4_4_4__2025-02-12-xxxxxx contain the channel frequency response, with dimensions of 4×4×4×9285×14 for the D-band and 4×4×4×8092×14 for the W-band. The first dimension corresponds to the receiver uniform linear array (ULA). The second and third dimensions (4×4) represent the transmitter uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (9285 for the D-band and 8092 for the W-band). The fifth dimension (14) corresponds to the different positions at which the transmitting URA was placed., Grant PID2022-136869NB-C32 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF/EU.”

The geometric data of files bevelgear1.txt, bevelgear2.txt, bevelgear3.txt and bevelgear4.txt were generated using IGD (Integrated Gear Design), an in-house software whose generation methods are based on the book "Litvin, F.L., Fuentes, A., Gear Geometry and Applied Theory, Cambridge University Press, 2004, ISBN 0521815177, New York" and on the methodology described in the related publication (http://hdl.handle.net/10317/24399). The function data of files fig13a.txt, fig13b.txt, fig13c.txt, fig13d.txt, fig14a.txt, fig14b.txt, fig14c.txt, fig14d.txt, fig15a.txt, fig15b.txt, fig15c.txt and fig15d.txt were generated using IGD based on the methodology described in the related publication (http://hdl.handle.net/10317/24399). The function data of files fig16.txt, fig17a.txt, fig17b.txt, fig19a.txt, fig19b.txt, fig21a.txt, fig21b.txt, fig22a.txt and fig22b.txt were generated using a specialized finite element analysis software (not relevant for visualization of the results) and postprocessing them in IGD. Files bevelgear*.txt can be imported and visualized using a user-created program considering the structure of the data described in the Summary section. Files fig*.txt can be visualized using the package TIKZ (\usepackage{tikz}) in the preamble of a Latex document., The dataset is comprised of text files. Four files contain geometric data and twenty one files contain function data. The geometric data include coordinates x, y and z, in mm, of surface points for both tooth sides of one gear tooth as follows: - 11 points along the longitudinal direction. - 15 points along the profile direction. - 8 points along the fillet direction. The function data include pairs of values corresponding to the graphics displayed in several figures of the related publication (http://hdl.handle.net/10317/24399). The graphics can illustrate tooth contact analysis results (kinematic transmission errors in arcsec) and stress analysis results (loaded transmission errors in arcsec, maximum contact pressures in MPa and maximum principal stresses in MPa)., Research project PID2023-152913NB-I00 funded by MICIU/AEI/10.13039/501100011033 and FEDER, UE.

OpenMC was evaluated over the open-source bLEO network emulator using controlled packet-level Multi-Connectivity and FEC experiments. The dataset contains 120 runs for the Fig. 2 delay-asymmetry campaign, 120 runs for the Fig. 3 scheduling campaign, 25 frozen Reed–Solomon rate-study runs, and 10 frozen RaptorQ rate-study runs. For the latency experiments, per-block measurements are first averaged within each independent run, and the resulting run-level observations are used to compute the reported means and two-sided 95% Student-t confidence intervals. The sustainable-rate study characterizes the complete experimental datapath rather than an intrinsic codec-only throughput limit. This institutional UPCT deposit preserves the experimental dataset and provides an expanded standalone README.txt with additional documentation of processed and raw CSV variables. Funding: project PID2023-148214OB-C21, funded by MICIU/AEI/10.13039/501100011033 and ERDF/EU., This dataset contains the raw and processed experimental data, configuration files, execution metadata, analysis and validation scripts, and final figures supporting the experimental evaluation of OpenMC, an open-source framework for packet-level experimentation with Multi-Connectivity (MC) and Forward Error Correction (FEC). The dataset supports four main evaluations: (i) the comparison of Reed–Solomon (RS) and systematic RaptorQ (RQ) under increasing delay asymmetry using Default scheduling; (ii) the comparison of RaptorQ Quality-based and Adaptive scheduling policies; (iii) the characterization of computational and packet-processing overhead; and (iv) the evaluation of the sustainable offered rate of the complete containerized experimental datapath. The archive includes per-block and run-level measurements, processed numerical results, experimental manifests, software and environment provenance, frozen configurations, reproduction and validation scripts, and the final publication figures. The accompanying README.txt provides a detailed description of the dataset structure, methodology, variables, units, and relationships between raw and processed data., This dataset was generated as part of project PID2023-148214OB-C21, funded by MICIU/AEI/10.13039/501100011033 and by ERDF/EU.

Propagation through the laboratories The files named P1_medidas1_6_5_4096_2024-10-07-xxxxxx contains the channel frequency response, with dimensions of 1×5×5×4096×19 . The first dimension corresponds to the single transmitter antenna. The second and third dimensions (5×5) represent the receiver uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (4096). The fifth dimension (23) corresponds to the different positions at which the transmitting was placed in the laboratory (Lab_02_11). The correspondence between the measurement files and the transmitter positions inside the different laboratories is defined as follows: P1_medidas1_6_5_4096_2024-10-07-130934 Lab_02_11 P2_medidas1_6_5_4096_2024-10-07-134433 P3_medidas1_6_5_4096_2024-10-07-135429 Pos1_medidas1_6_5_4096_2024-10-10-160350%Lab_2_23 Pos2_medidas1_6_5_4096_2024-10-10-161621 Pos3_medidas1_6_5_4096_2024-10-10-162637 Pos4_medidas1_6_5_4096_2024-10-10-163537 Pos5_medidas1_6_5_4096_2024-10-10-164438 Pos6_medidas1_6_5_4096_2024-10-10-165238 Pos7_medidas1_6_5_4096_2024-10-10-170113 Pos8_medidas1_6_5_4096_2024-10-10-182938 Pos1_medidas1_6_5_4096_2024-10-10-171309 %lab_2_10 Pos2_medidas1_6_5_4096_2024-10-10-172127 Pos3_medidas1_6_5_4096_2024-10-10-172926 Pos4_medidas1_6_5_4096_2024-10-10-173812 Pos5_medidas1_6_5_4096_2024-10-10-174722 Pos6_medidas1_6_5_4096_2024-10-10-175615 Pos7_medidas1_6_5_4096_2024-10-10-180734 Pos8_medidas1_6_5_4096_2024-10-10-181756 The MATLAB script ELDI_partition_Loss_Full_BW computes the parameters of the FI with partition loss model across the entire FR3 bandwidth (7–24 GHz). The MATLAB script ELDI_partition_Loss_subbands computes the parameters of the FI with partition loss model for the FR3 sub-bands: (7.125–8.4 GHz, 10–10.5 GHz, 10.7–13.25 GHz, 14.8–15.35 GHz, and 21.2–23.6 GHz). Propagation along the corridor The files named P1_PC_medidas1_6_5_4096_2024-10-08-xxxxxx contains the channel frequency response, with dimensions of 1×5×5×4096×24 . The first dimension corresponds to the single transmitter antenna. The second and third dimensions (5×5) represent the receiver uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (4096). The fifth dimension (24) corresponds to the different positions at which the transmitting was placed along the corridor. The correspondence between the measurement files and the transmitter positions along the corridor is defined as follows: P1_PC_medidas1_6_5_4096_2024-10-08-103450 Tx pos. 1 P2_PC_medidas1_6_5_4096_2024-10-08-105003 Tx pos. 2 P3_PC_medidas1_6_5_4096_2024-10-08-110545 Tx pos. 3 P4_PC_medidas1_6_5_4096_2024-10-08-112110 Tx pos. 4 P5_PC_medidas1_6_5_4096_2024-10-08-113534 Tx pos. 5 P6_PC_medidas1_6_5_4096_2024-10-08-115011 Tx pos. 6 P7_PC_medidas1_6_5_4096_2024-10-08-120556 Tx pos. 7 P8_PC_medidas1_6_5_4096_2024-10-08-122717 Tx pos. 8 P9_PC_medidas1_6_5_4096_2024-10-08-124217 Tx pos. 9 P10_PC_medidas1_6_5_4096_2024-10-08-125957 Tx pos. 10 P11_PC_medidas1_6_5_4096_2024-10-08-153253 Tx pos. 11 P12_PC_medidas1_6_5_4096_2024-10-08-155009 Tx pos. 12 P13_PC_medidas1_6_5_4096_2024-10-08-160433 Tx pos. 13 P14_PC_medidas1_6_5_4096_2024-10-08-161839 Tx pos. 14 P15_PC_medidas1_6_5_4096_2024-10-08-163704 Tx pos. 15 P16_PC_medidas1_6_5_4096_2024-10-08-165323 Tx pos. 16 P17_PC_medidas1_6_5_4096_2024-10-08-170828 Tx pos. 17 P18_PC_medidas1_6_5_4096_2024-10-08-133236 Tx pos. 18 P19_PC_medidas1_6_5_4096_2024-10-08-172615 Tx pos. 19 P20_PC_medidas1_6_5_4096_2024-10-08-174148 Tx pos. 20 P21_PC_medidas1_6_5_4096_2024-10-08-175618 Tx pos. 21 P22_PC_medidas1_6_5_4096_2024-10-08-181148 Tx pos. 22 P23_PC_medidas1_6_5_4096_2024-10-08-182903 Tx pos. 23 P24_PC_medidas1_6_5_4096_2024-10-08-184431 Tx pos. 24 The MATLAB script ELDI_PC computes the parameters of the partition FI model across the entire FR3 bandwidth (7–24 GHz) for the corridor scenario. Functions The function calcula_L_Wall_FI computes the parameters of the partition FI loss model. The function calcula_L_Wall_CI computes the parameters of the partition CI loss model. The function coherence_bandwidth_frequency computes the coherence bandwidth., This dataset is composed of a set of measurements and the code to analyze the measurements. The files named P1_medidas1_6_5_4096_2024-10-07-xxxxxx contains the channel frequency response, with dimensions of 1×5×5×4096×19 . The first dimension corresponds to the single transmitter antenna. The second and third dimensions (5×5) represent the receiver uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (4096). The fifth dimension (23) corresponds to the different positions at which the transmitting was placed in the laboratory (Lab_02_11). The files named P1_PC_medidas1_6_5_4096_2024-10-08-xxxxxx contains the channel frequency response, with dimensions of 1×5×5×4096×24 . The first dimension corresponds to the single transmitter antenna. The second and third dimensions (5×5) represent the receiver uniform rectangular array (URA). The fourth dimension contains the frequency samples measured by the VNA (4096). The fifth dimension (24) corresponds to the different positions at which the transmitting was placed along the corridor.

Key Characteristics: Single-Class Session Policy: The dataset is built on a design where each capture session contains exclusively benign traffic or a single attack family. This prevents temporal overlap and ensures that every bi-flow has an unambiguous label. Modern Traffic and APIs: The benign traffic simulates enterprise-grade services (HTTP/S, DNS, SSH, MySQL) and includes modern API traffic (REST, GraphQL, SOAP), which is critical for representing contemporary edge environments. Diverse Threat Coverage: It incorporates 15 distinct attack families, including volumetric attacks (DDoS/DoS), reconnaissance (Portscan), web and API exploits, brute force, DNS abuse, MITM, NIDS evasion, and persistence vectors like C2/beaconing and exfiltration. CICFlowMeter Integration: The raw traffic was processed using CICFlowMeter (version 4.0) to generate bidirectional flows (bi-flows). It provides a standardized schema of 80 statistical features per flow, allowing for lightweight detection without payload inspection. Structure and Scale: The dataset comprises approximately 4.6 million bi-flows distributed across 16 independent single-class CSV files. This modular structure allows researchers to construct custom distributions and prevents temporal leakage during model training. Realistic Imbalance: The data reflects a realistic traffic distribution where benign activity dominates, with a ratio of approximately 1.3:1 between benign and malicious flows., Intrusion Detection Systems (IDS) for IoT and edge environments require datasets with unambiguous labels. Existing corpora often mix benign and malicious traffic within the same capture window, producing ambiguous flow labels that distort model evaluation. This work introduces the TRUST Lab Dataset, a flow-based traffic corpus designed under a single-class session policy: each capture contains exclusively benign traffic or a single attack family, preventing temporal overlap and ensuring label integrity at the bi-flow level. The dataset was generated in an operational testbed reproducing enterprise-grade services (HTTP/S, DNS, email, SSH, SNMP, NTP, MySQL) and modern APIs (REST, GraphQL, SOAP), combined with 15 attack families spanning DDoS/DoS, port scanning, brute force, web/API exploits, DNS abuses, MITM, NIDS evasion, tunneling/exfiltration, C2/beaconing, TLS/SSL anomalies, buffer overflow, and slowloris. Traffic was processed with CICFlowMeter into 16 single-class CSV files totaling ~4.6million bi-flows with 80 features per flow. Comprehensive statistical analyses (distributions, correlation, ANOVA, PCA) confirm discriminative signal without payload inspection. A binary meta-classifier achieves ROC-AUC 0.9676 and recall 0.95, validating TRUST Lab's utility for lightweight edge-oriented IDS evaluation., This research is part of the project TRUST Lab, R&D&I Laboratory in Cybersecurity, Privacy, and Secure Communications, financed by European Union NextGeneration-EU, the Recovery Plan, Transformation and Resilience, through INCIBE.

Supporting material associated with the article submitted to the Journal of Hydraulic Engineering (ASCE). This file includes Appendix S1–S3 removed from the manuscript., This record contains the supplementary material associated with the article “Free-surface maps and profiles of hydraulic jumps measured with a depth camera,” accepted for publication in the Journal of Hydraulic Engineering (ASCE). The file compiles three appendices removed from the manuscript for editorial length compliance. Appendix S1 presents air-concentration profiles and average air-concentration distributions used to support the characterization of partially developed inflow conditions. Appendix S2 documents the phase-space thresholding filter method applied to the depth-camera time series, including the governing equations and spike-replacement procedure. Appendix S3 provides additional free-surface topography, fluctuation maps, longitudinal and transverse profiles, and supplementary comparisons with previous studies for hydraulic jumps with Fr1 = 4.45, 5.97, 8.33, and 9.11. This material complements the main article and facilitates transparency, reproducibility, and reuse of the supporting analyses., Grant PID2022-142037OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, by the “European Union”.

This dataset was created based on the FLAME dataset, namely the ninth and tenth repositories which contain 2,003 fire frames with a resolution of 3480x2160 in JPEG format and their corresponding masks, respectively. The folder dataset contains a copy of the original dataset divided into training (first 80% of the samples) and validation (last 20%), where the labels have been converted from the masks in the original dataset to the YoLo bounding boxes format. The folder fire_tracking.zip contains the results after applying object tracking to the fires in the dataset, with a file for each fire detected wich contains the file name and bouding box of every time that fire is detected. This tracking was manually supervised, with spetial interest in the validation part of the dataset. The process is described in the Methods section of this dataset. The file fires_tracked.mp4 represents shows the dataset at a rate of 10 frames per second, showing the fire ids (i.e. the results of the fire tracking) of the validation part of the dataset., This work was supported by the grant PID2023-148214OB-C21 funded by MICIU/AEI/10.13039/501100011033 and by FEDER/EU. This work was also supported by the grants PCI2024-153485 and PDC2025-165710-C22 funded by MICIU/AEI/10.13039/501100011033 and by the European Union. This research was also funded by the PRIMA Programme under Grant Agreement No. 2431 (FUSION). The work of Francisco-Jose Alvarado-Alcon was supported by the Spain’s Ministry of Universities under Grant FPU22/00316.