Data Analysis and Cybersecurity
DATA ANALYSIS AND CYBERSECURITY
The Data Analysis and Cybersecurity research team is focused on researching, developing and transferring innovative data-driven decision-making solutions to the industry, research centers and society. To this end, the Group investigates intelligent systems, designing, developing and applying machine learning techniques, data mining and Big Data to real problems.
The objective is therefore to make it facilitate companies, technology centers and socio-economic agents to face new challenges and build lasting competitive advantages, with control, analysis and interpretation of the data being the basis for providing differential added value to products and services.
The Group focuses its activities on four lines of research (Information and Communication Security, Industrial Processes, Advanced Manufacturing, and Health Industry), three of which are strategic priorities of the Basque Government (Advanced Manufacturing (which encompasses industrial processes), Energy and Biosciences/Health. Industrial Cybersecurity is an activity that cuts across all of them.
Lines of research and knowledge areas
Information and Communications Security
The objective of this research line is to face the new challenges posed by the most recent developments and uses of information technologies, providing solutions to improve trustworthiness in the new ICT landscape through research in new secure and reliable technologies. Our research group is contributing in areas such as: social network security, cyber-physical systems security, SCADA/ICS security, or device and mobile network security.
Intelligent Systems for Industrial Processes
In this line of research, the team focuses its activity on improving processes where automation is involved (metal processing, water purification, foundry processes, injection,...). It makes use of information at the process level, and seeks the optimization of parameters, the process, and the detection of anomalies in the process.
Intelligent Systems for the Healthcare Industry
It focuses on data analysis to aid decision making and improve the quality of patients’ life and healthcare professionals work. To this end, techniques are mainly used to identify patterns and predict human behaviour to help prevent disease or improve the quality of life. Heterogeneous data sources are used following the Big Data paradigm, with medical history, personal data or environmental data being some examples.
Intelligent Systems for Advanced Manufacturing
The Group works to provide manufacturing processes with greater intelligence, monitoring and prediction of manufacturing faults in manufacturing processes (with big data streaming techniques and time series prediction algorithms), and proactive maintenance techniques for manufacturing elements (with root cause analysis, remaining useful life identification and optimization). Data gathered directly from sensors installed in the manufacturing elements is used, as well as CNC, or PLC elements.
Offers of employment and doctorate
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