MaLPIS

About Project

Aprendizagem Automática para Deteção de Ataques e Identificação de Perfis Segurança na Internet

Acronym

MaLPIS

Responsible

Ricardo Santos Morla

Status

Concluded

Start

January 1, 2018

End

January 30, 2022

Effective End

January 30, 2022

Global Budget

€238,790.78

Financing

€36,615.65

Members

Team Leaders

Maria Paula de Pinho de Brito Duarte Silva

I am Associate Professor at the School of Economics of the University of Porto, where I teach Statistics and Multivariate Data Analysis, at undergraduate and post-graduate (Master, PhD) levels, and member of the Artificial Intelligence and Decision Support Lab (LIAAD) of INESC-TEC. I hold a doctorate degree in Applied Mathematics from the University of Paris Dauphine (1991).

My current research focuses on the analysis of multidimensional complex data, known as symbolic data - data representing inherent variability, in the form of intervals or distributions - for which I develop statistical approaches and multivariate analysis methodologies. I am generally interested in multivariate data analysis, with particular incidence in clustering methods.

Team Members

Maria Paula de Pinho de Brito Duarte Silva

Sónia Manuela Mendes Dias

Associated Centres

High-Assurance Software

At the High-Assurance Software Laboratory (HASLab), we improve practice through theory, creating and implementing software that goes beyond mere functionality: we ensure it is correct, resilient, and secure against failures and attacks. Our team of researchers, scientists, and engineers has proven expertise in software engineering, developing methods and tools to design and integrate robust software; in distributed systems, exploring distribution and replication to ensure scalability and reliability; and in information security, addressing cybersecurity challenges and improving systems with advanced, secure cryptographic protocols, thus minimising vulnerabilities. With a multidisciplinary approach supported by solid theoretical principles, we develop innovative solutions for critical software, secure cloud infrastructures, and privacy-aware big data management, driving scientific advancement, innovation, and high-level consultancy. In addition, we complement our core expertise with work in human-computer interaction, programming languages, computational mathematics, and quantum computing - because we believe the future of trustworthy software is built on knowledge and innovation.

Artificial Intelligence and Decision Support

Our Laboratory of Artificial Intelligence and Decision Support (LIAAD) conducts research in the fields of Artificial Intelligence, Machine Learning, Data Science, and Modelling. These areas are cross-cutting and apply to all sectors of society and the economy. The vast amounts of data being collected, alongside the ubiquity of digitalisation and sensorisation, are increasingly creating opportunities and challenges for automating decision support. The combination of Machine Learning and complex models is transforming the economy, healthcare, justice, industry, science, public administration, and education. This encourages us to invest in diverse technological and scientific approaches and perspectives. Our overarching strategy is to explore the flow and diversification of data, and to invest in research lines that will lead to the development of applied Artificial Intelligence foundations and models that are responsible and human centred.