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SDRS: A new lossless dimensionality reduction for text corpora 

Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (Elsevier Ltd., 2020)
In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, ...
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Deep packet inspection for intelligent intrusion detection in software-defined industrial networks: A proof of concept 

Sainz Oruna, Markel; Garitano, Iñaki; Iturbe, Mikel; Zurutuza, Urko (Oxford Academic, 2020)
Specifically tailored industrial control systems (ICSs) attacks are becoming increasingly sophisticated, accentuating the need of ICS cyber security. The nature of these systems makes traditional IT security measures not ...
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Low delay network attributes randomization to proactively mitigate reconnaissance attacks in industrial control systems 

Etxezarreta, Xabier; Garitano, Iñaki; Iturbe, Mikel; Zurutuza, Urko (Springer, 2023)
Industrial Control Systems are used in a wide variety of industrial facilities, including critical infrastructures, becoming the main target of multiple security attacks. A malicious and successful attack against these ...
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A methodology and experimental implementation for industrial robot health assessment via torque signature analysis 

Izagirre, Unai; andonegui, imanol; Egea, Aritz; Zurutuza, Urko (MDPI AG, 2020)
This manuscript focuses on methodological and technological advances in the field of health assessment and predictive maintenance for industrial robots. We propose a non-intrusive methodology for industrial robot joint ...
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Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data 

Serradilla, Oscar; Zugasti, Ekhi; Zurutuza, Urko (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 ...
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Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects 

Serradilla, Oscar; Zugasti, Ekhi; Zurutuza, Urko (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 ...
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A practical and synchronized data acquisition network architecture for industrial robot predictive maintenance in manufacturing assembly lines 

Izagirre, Unai; andonegui, imanol; Zurutuza, Urko (Elsevier Ltd., 2021)
This manuscript presents a methodology and a practical implementation of a network architecture for industrialrobot data acquisition and predictive maintenance. We propose a non-intrusive and scalable robot signalextraction ...
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Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge 

Serradilla, Oscar; Zugasti, Ekhi; Zurutuza, Urko (Taylor and Francis, 2022)
The 4th industrial revolution has connected machines and industrial plants, facilitating process monitoring and the implementation of predictive maintenance (PdM) systems that can save up to 60% of maintenance costs. ...
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Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation 

Sáez-de-Cámara, Xabier; Zurutuza, Urko (IEEE, 2023)
The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising results for intrusion detection; however, the ...
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Multi-objective evolutionary optimization for dimensionality reduction of texts represented by synsets 

Velez de Mendizabal, Iñaki; Ezpeleta, Enaitz; Zurutuza, Urko (PeerJ, 2023)
Despite new developments in machine learning classification techniques, improving the accuracy of spam filtering is a difficult task due to linguistic phenomena that limit its effectiveness. In particular, we highlight ...
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a0e0c864f710057ff478bee93b061c01 (16)
2091789a0efe4678b167df6999ac9f34 (4)8002cbdf4d2bfb84463ca27cdf6192ac (4)d91110e67da92a88f1d0dfad5e0934a8 (4)0450c040dfb1b80c9c3308e40a3eaf5d (3)3a2df8b70cbacf7866ab05906556f78c (3)625a7f9e2b226e958788bcdcd3b02aef (3)bcce90727237eac3d600e78c870b9b62 (3)f19899d4ad9abd2b7c53f217f72b56f9 (3)fc1a108b0cdc3f4b9f10c619be1bbffc (3)... View MoreSubjectpredictive maintenance (5)Software defined networking (4)Botnet (2)Industrial Control Systems (2)Industrial control systems (2)Industry 4.0 (2)Machine learning (2)Multi-objective evolutionary algorithms (2)Network security (2)ODS 9 Industria, innovación e infraestructura (2)... View MoreDate Issued2023 (6)2020 (4)2021 (3)2022 (2)2024 (1)Has File(s)Yes (16)

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