Browsing by Research Group "Análisis de datos y ciberseguridad"
Now showing items 1-20 of 49
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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 ... -
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 ... -
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, ... -
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 ... -
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 ... -
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
(Springer Science+Business Media, LLC, 2022)Given the growing amount of industrial data in the 4th industrial revolution, deep learning solutions have become popular for predictive maintenance (PdM) tasks, which involve monitoring assets to anticipate their requirements ... -
Detection and Visualization of Android Malware Behavior
(Hindawi Publishing Corporation, 2016)Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious ... -
Different approaches for the detection of SSH anomalous connections
(Oxford Academic, 2016)The Secure Shell Protocol (SSH) is a well-known standard protocol, mainly used for remotely accessing shell accounts on Unix-like operating systems to perform administrative tasks. As a result, the SSH service has been an ... -
Drilling test data from new and worn bits
(2019)This directory contains the raw data acquired by Mondragon Unibertsitatea during the execution of drilling tests. These data were used to obtain the results presented in the article "The capacity of statistical features ... -
Early diagnosis of disorders based on behavioural shifts and biomedical signals
(Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2017)There are many disorders that directly affect people’s behaviour. The people that are suffering from such a disorder are not aware of their situation, and too often the disorders are identified by relatives or co-workers ... -
Estimación cualitativa de la rugosidad mediante algoritmos de aprendizaje automático en una operación de taladrado
(Federación de Asociaciones de Ingenieros Industriales de España, 2020) -
From KPI Dashboards to Advanced Visualization
(River Publishers, 2018) -
Fuzzing the Internet of Things: A Review on the Techniques and Challenges for Efficient Vulnerability Discovery in Embedded Systems
(IEEE, 2021)With a growing number of embedded devices that create, transform and send data autonomously at its core, the Internet-of-Things (IoT) is a reality in different sectors such as manufacturing, healthcare or transportation. ... -
How to Quantify the Security Level of Embedded Systems? A Taxonomy of Security Metrics
(IEEE, 2020)Embedded Systems (ES) development has been historically focused on functionality rather than security, and today it still applies in many sectors and applications. However, there is an increasing number of security threats ... -
Implementation of a Reference Architecture for Cyber Physical Systems to support Condition Based Maintenance
(2018)This paper presents the implementation of a refer-ence architecture for Cyber Physical Systems (CPS) to supportCondition Based Maintenance (CBM) of industrial assets. The article focuses on describing how the MANTIS ... -
Impregnation quality diagnosis in Resin Transfer Moulding by machine learning
(Elsevier Ltd., 2021)In recent years, several optimization strategies have been developed which reduce the overall defectiveness of the RTM manufactured part. RTM filling simulations showed that, even using optimized injection strategies, local ... -
Incorporation of Synthetic Data Generation Techniques within a Controlled Data Processing Workflow in the Health and Wellbeing Domain
(MDPI, 2022)To date, the use of synthetic data generation techniques in the health and wellbeing domain has been mainly limited to research activities. Although several open source and commercial packages have been released, they have ...
