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Publicações

2023

Data Stream Analytics

Autores
Aguilar Ruiz, S; Bifet, A; Gama, J;

Publicação
Analytics

Abstract
[No abstract available]

2023

The syntactic side of autonomous categories enriched over generalised metric spaces

Autores
Dahlqvist, F; Neves, R;

Publicação
Log. Methods Comput. Sci.

Abstract

2023

Determinants of students' use of food consumption resources available at the University of Porto

Autores
Nova, Lúcia; Poínhos, Rui; Bruno M P M Oliveira; Rocha, Ada; Afonso, Cláudia;

Publicação

Abstract

2023

Robot at Factory Lite - A Step-by-Step Educational Approach to the Robot Assembly

Autores
Luiz, LE; Pilarski, L; Baidi, K; Braun, J; Oliveira, A; Lima, J; Costa, P;

Publicação
ROBOT2022: FIFTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1

Abstract
In a robotics scope, an excellent way to test and improve knowledge is through competitions. In other words, it is possible to follow the results in practice, compare them with the development of other teams and improve the current solutions. The Robot At Factory Lite proposal simulates an Industry 4.0 warehouse scenario, applying education through Science, Technology, Engineering, and Mathematics (STEM) methodology, where the participants have to work on a solution to overcome its challenges. Thus, this article presents an initial electromechanical proposal, which is the basis for developing robots for this competition. The presented main concepts aim to inform the possibilities of using the robot's parts and components. Thus, an idea can be sketched in the participants' minds, inspiring them to use their imagination and knowledge through the presentation of this model.

2023

Skynet: a Cyber-Aware Intrusion Tolerant Overseer

Autores
Freitas, T; Soares, J; Correia, ME; Martins, R;

Publicação
2023 53RD ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS - SUPPLEMENTAL VOLUME, DSN-S

Abstract
The increasing level of sophistication of cyber attacks which are employing cross-cutting strategies that leverage multi-domain attack surfaces, including but not limited to, software defined networking poisoning, biasing of machine learning models to suppress detection, exploiting software (development), and leveraging system design deficiencies. While current defensive solutions exist, they only partially address multi-domain and multi-stage attacks, thus rendering them ineffective to counter the upcoming generation of attacks. More specifically, we argue that a disruption is needed to approach separated knowledge domains, namely Intrusion Tolerant systems, cybersecurity, and machine learning. We argue that current solutions tend to address different concerns/facets of overlapping issues and they tend to make strong assumptions of supporting infrastructure, e.g., assuming that event probes/metrics are not compromised. To address these issues, we present Skynet, a platform that acts as a secure overseer that merges traditional roles of SIEMs with conventional orchestrators while being rooted on the fundamentals introduced by previous generations of intrusion tolerant systems. Our goal is to provide an open-source intrusion tolerant platform that can dynamically adapt to known and unknown security threats in order to reduce potential vulnerability windows.

2023

Using Balancing Methods to Improve Glycaemia-Based Data Mining

Autores
Machado, D; Costa, VS; Brandão, P;

Publicação
Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2023, Volume 5: HEALTHINF, Lisbon, Portugal, February 16-18, 2023.

Abstract

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