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Now showing items 11-20 of 21
Novel email spam detection method using sentiment analysis and personality recognition
(Oxford Academic, 2020)
Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to ...
Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge
(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. ...
Deep packet inspection for intelligent intrusion detection in software-defined industrial networks: A proof of concept
(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 ...
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 ...
Estudio de modelado de perifericos para habilitar emulaciones de firmware embebido
(Tecnalia. Incibe, 2022)
Los sistemas embebidos aumentan cada vez más en número y con ello también lo hacen los ataques dirigidos a estos. Uno de los factores clave para reducir la superficie de ataque es descubrir y corregir vulnerabilidades en ...
Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation
(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 ...
Multi-objective evolutionary optimization for dimensionality reduction of texts represented by synsets
(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 ...
Deobfuscating leetspeak with deep learning to improve spam filtering
(UNIR - Universidad Internacional de La Rioja, 2023)
The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...
Federated Explainability for Network Anomaly Characterization
(ACM, 2023)
Machine learning (ML) based systems have shown promising results for intrusion detection due to their ability to learn complex patterns. In particular, unsupervised anomaly detection approaches offer practical advantages ...
Towards manufacturing robotics accuracy degradation assessment: A vision-based data-driven implementation
(Elsevier, 2021)
In this manuscript we report on a vision-based data-driven methodology for industrial robot health assessment. We provide an experimental evidence of the usefulness of our methodology on a system comprised of a 6-axis ...