Zerrendatu honen arabera: egilea "a0e0c864f710057ff478bee93b061c01"
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Actas de las Cuartas Jornadas Nacionales de Investigación en Ciberseguridad. Donostia-San Sebastián, Gipuzkoa, 13-15 de Junio, 2018
Jornadas Nacionales de Investigación en Ciberseguridad (JNIC) (Mondragon Unibertsitateko Zerbitzu Editoriala, 2018) -
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 ... -
Aleatorización de direcciones IP para mitigar ataques de reconocimiento de forma proactiva en sistemas de control industrial
Etxezarreta, Xabier; Garitano, Iñaki; Iturbe, Mikel; Zurutuza, Urko (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 ... -
An attribute oriented induction based methodology to aid in predictive maintenance: anomaly detection, root cause analysis and remaining useful life
Fernández Anakabe, Javier (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
Garitano, Iñaki (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
Larrinaga, Felix; Zugasti, Ekhi; Garitano, Iñaki; Zurutuza, Urko (Sage Journals, 2019) -
Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
Zurutuza, Urko (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
Zurutuza, Urko (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
Zurutuza, Urko; Uribeetxeberria, Roberto; Azketa, E.; Gil, G.; Lizarraga Durandegui, Jesús María; Fernández Arrieta, Miguel (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 ... -
Cyber Physical System Based Proactive Collaborative Maintenance
Zurutuza, Urko; Uribeetxeberria, Roberto (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
Zurutuza, Urko (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 ... -
Data-Driven Anomaly Detection in Industrial Networks
Iturbe, Mikel (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2017)Since the conception of the first Programmable Logic Controllers (PLCs) in the 1960s, Industrial Control Systems (ICSs) have evolved vastly. From the primitive isolated setups, ICSs have become increasingly interconnected, ... -
Data-Driven Industrial Human-Machine Interface Temporal Adaptation for Process Optimization
Reguera-Bakhache, Daniel; Garitano, Iñaki; Uribeetxeberria, Roberto; Cernuda, Carlos; Zurutuza, Urko (IEEE, 2020)The application of Artificial Intelligence (AI) into Industrial Human-Machine Interfaces (HMIs) moved old systems with physical buttons and analogue actuators into adaptive interaction models and context-based self adjusted ... -
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 ... -
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 ... -
Deobfuscating leetspeak with deep learning to improve spam filtering
Velez de Mendizabal, Iñaki; Vidriales Mazorriaga, Xabier; Ezpeleta, Iñigo; Zurutuza, Urko (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 ... -
Detection and Visualization of Android Malware Behavior
Zurutuza, Urko; Uribeetxeberria, Roberto (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
Zurutuza, Urko (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 ... -
Dynamic DNS Request Monitoring of Android Applications via networking
Zurutuza, Urko; Uribeetxeberria, Roberto (IEEE, 2018)Smart devices are very popular and are becoming ubiquitous in the modern society, with Android OS as the most widespread operating system on current smartphones/tablets. However, malicious applications is one of the major ... -
Dynamic monitoring of Android malware behavior: a DNS-based approach
Somarriba jarquin, Oscar Manuel (Mondragon Unibertsitatea. Goi Eskola Politeknikoa, 2019)The increasing technological revolution of the mobile smart devices fosters their wide use. Since mobile users rely on unofficial or thirdparty repositories in order to freely install paid applications, lots of security ...
