Zerrendatu honen arabera: ikerketa taldea "Análisis de datos y ciberseguridad"
118-tik 1-20 emaitza erakusten
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Active Power Optimization of a Turning Process by Cutting Conditions Selection: A Q-Learning Approach
(IEEE, 2022)In the context of Industry 4.0, the optimization of manufacturing processes is a challenge. Although in recent years many of the efforts have been in this direction, there is still improvement opportunities in these ... -
Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data
(MDPI, 2021)Predictive maintenance (PdM) has the potential to reduce industrial costs by anticipating failures and extending the work life of components. Nowadays, factories are monitoring their assets and most collected data belong ... -
An Adaptive Industrial Human-Machine Interface to Optimise Operators Working Performance
(IEEE, 2021)Adaptive User Interfaces (AUI) have the potential to deliver advantageous solutions for a wide range of industrial applications. Their ability to adapt to operator interaction patterns and achieve a more personalised ... -
Aleatorización de direcciones IP para mitigar ataques de reconocimiento de forma proactiva en sistemas de control industrial
(Tecnalia. Incibe, 2022)Los sistemas de control industrial se utilizan en una gran variedad de procesos físicos, incluidas las infraestructuras críticas, convirtiéndose en el principal objetivo de múltiples ataques de seguridad. Un ataque ... -
Artificial Neural Network Based Reinforcement Learning for Wind Turbine Yaw Control
(MDPI AG, 2019)This paper introduces a novel data driven yaw control algorithm synthesis method based on Reinforcement Learning (RL) for a variable pitch variable speed wind turbine. Yaw control has not been extendedly studied in the ... -
An attribute oriented induction based methodology to aid in predictive maintenance: anomaly detection, root cause analysis and remaining useful life
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2019)Predictive Maintenance is the maintenance methodology that provides the best performance to industrial organisations in terms of time, equipment effectiveness and economic savings. Thanks to the recent advances in technology, ... -
Behavioral modeling for anomaly detection in industrial control systems
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2013)In 1990s, industry demanded the interconnection of corporate and production networks. Thus, Industrial Control Systems (ICSs) evolved from 1970s proprietary and close hardware and software to nowadays Commercial Off-The-Shelf ... -
Bending rigidity, sound propagation and ripples in flat graphene
(Springer Nature, 2024)Many of the applications of graphene rely on its uneven stiffness and high thermal conductivity, but the mechanical properties of graphene—and, in general, of all two-dimensional materials—are still not fully understood. ... -
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
(MDPI, 2023)In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is ... -
A Big Data implementation of the MANTIS Reference Architecture for Predictive Maintenance
(Sage Journals, 2019) -
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process
(Springer Verlag, 2019)Industrial processes are being developed under a new scenario based on the digitalisation of manufacturing processes.Through this, it is intended to improve the management of resources, decision-making, ... -
Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
(Elsevier, 2023)There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover, the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse hardware and software, and being ... -
A collaborative framework for android malware detection using DNS & dynamic analysis
(IEEE, 2018)Nowadays, with the predominance of smart devices such as smartphones, mobile malware attacks have increasingly proliferated. There is an urgent need of detecting potential malicious behaviors so as to hinder them. Furthermore, ... -
Combined data mining approach for intrusion detection
(Scitepress, 2007)This paper presents the results of the project MIAU, a data mining approach for intrusion detection alert correlation. MIAU combines different data mining techniques in order to properly solve some existing problems in the ... -
Comparative assessment of synthetic time series generation approaches in healthcare: leveraging patient metadata for accurate data synthesis
(Springer Nature, 2024)Background Synthetic data is an emerging approach for addressing legal and regulatory concerns in biomedical research that deals with personal and clinical data, whether as a single tool or through its combination with ... -
Cookies from the Past: Timing Server-Side Request Processing Code for History Sniffing
(ACM, 2020)Cookies were originally introduced as a way to provide state awareness to websites, and are now one of the backbones of the current web. However, their use is not limited to store the login information or to save the current ... -
Critical Analysis of the Suitability of Surrogate Models for Finite Element Method Application in Catalog-Based Suspension Bushing Design
(IEEE, 2020)This work presents a critical analysis of the suitability of surrogate models for finite element method application. A case study of a finite element method (FEM) structural problem was selected in order to test the ... -
Cyber Physical System Based Proactive Collaborative Maintenance
(IEEE, 2016)The aim of the MANTIS project is to provide a proactive maintenance service platform architecture based on Cyber Physical Systems. The platform will allow estimating future performance, predicting and preventing imminent ... -
Cybersecurity Evaluation Methodology based on Metrics for Industrial Embedded Systems
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2022)During the last decades, Embedded Systems (ESs) have evolved from isolated systems into a fully connected devices. Today, due to the development of processing capabilities, ESs have the ability to control or manage a wide ... -
Data minig approaches for analysis of worm activity toward automatic signature generation
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2007)En esta tesis se propone un marco para el análisis de tráfico no solicitado (como intentos de propagación de gusanos informáticos) recopilados por un sistema de monitorización de red. El análisis de esta información puede ...
