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Publications

2024

Common Techniques, Success Attack Factors and Obstacles to Social Engineering: A Systematic Literature Review

Authors
Lopes, A; Mamede, S; Reis, L; Santos, A;

Publication
Emerging Science Journal

Abstract
Knowledge of Social Engineering is crucial to prevent potential attacks related to organizational Information Security. The objective of this paper aims to identify the most common social engineering techniques, success attack factors, and obstacles, as well as the good practices and frameworks that could be adopted concerning their mitigation. As an analysis methodology, a Systematic Literature Review was carried out. The findings revealed that the discussion about SE attacks has increased and that the most imminent threat is phishing. Exploiting human vulnerabilities is a growing threat when the attack is not carried out directly through technical means. There continue to be more technical attacks than non-technical attacks. Encouraging organizational security prevention, like training, education, technical controls, process development, defense in detail, and the development of security policies, should be considered mitigating factors for the negative impact of SE attacks. Most SE frameworks/models are focused on attack techniques and methods, mostly on technical components, decorating human factor. As a novelty, we found the opportunity to develop a new framework that could improve coverage of the gaps found, supported on security international standards, that could help and support researchers in developing their work, understanding open research topics, and providing a clearer understanding of this type of threat. © 2024 by the authors. Licensee ESJ, Italy.

2024

Immersive Creation of Virtual Reality Training Experiences

Authors
Coelho, H; Monteiro, P; Gonçalves, G; Melo, M; Bessa, M;

Publication
IEEE ACCESS

Abstract
Virtual reality (VR) for training helps minimize risks and costs by allowing more frequent and varied use of experiential training experiences, leading to active and improved learning. However, creating VR training experiences is costly and time-consuming, requiring software development experts. Additionally, current authoring tools are desktop-oriented, which detaches the process of creating the immersive experience from experiencing it in a situated context. This paper presents the development of an immersive authoring tool designed to create immersive virtual environments that can be used to train operatives. The authoring tool can record and replay animations of each action the user performed that can later be used to instruct other users how the task should be performed. Participants were divided into two groups, and the proposed authoring tool was evaluated using usability, satisfaction, presence and cybersickness. Between groups, Independent T-tests revealed that there were no significant differences between expert and non-expert groups in any of the studied variables. Also, the results showed that the authoring tool had high usability and satisfaction, average presence, and low probability of cybersickness symptoms.

2024

Processos sistemáticos de extração e de consolidação da informação de elementos em modelos BIM para parametrização de artigos ProNIC

Authors
Teixeira, J; Guardão, L; Mêda, P; Moreira, J; Sousa, R; Sousa, H; Ribeiro, Y;

Publication
5º Congresso Português de Building Information Modelling Volume 1: ptBIM

Abstract

2024

RIFF: Inducing Rules for Fraud Detection from Decision Trees

Authors
Martins, JL; Bravo, J; Gomes, AS; Soares, C; Bizarro, P;

Publication
CoRR

Abstract

2024

Modeling and Optimizing Sugarcane-Livestock Integration Systems in Brazil

Authors
Dias, LR; Cardoso, F; Jimenez, CM; Marques, GO; Barioni, G; Barbosa, F; Mariano, P; Cunha, P; Bonomi, A;

Publication
Computer Aided Chemical Engineering

Abstract
The expansion of ethanol production in Brazil sparks several sustainability concerns, including debates on “food versus fuel”, the environmental impacts of monocultures, and indirect land-use change. Since livestock farming occupies a significantly greater area than sugarcane for ethanol production in Brazil and has a large yield gap, sugarcane-livestock integration can be a promising alternative. This integrated system considers crop production systems, biorefinery processing and meat production in both intensive and extensive livestock farming. Optimizing this system for both economic and environmental aspects can be challenging to implement and computationally expensive as this system's complexity arises from nonlinear subsystems and their intertwining input-output flows. For these reasons, this paper develops metamodels from detailed models to: (i) Optimize the extensive livestock farming, (ii) Optimize the confined animal feeding, and (iii) Optimize the integrated system. The main objective is to maximize the Net Present Value relative to investment. This study contributes to the literature by developing innovative models for ethanol-beef integrated production systems and methods for optimizing such systems to avoid negative externalities on food security and environmental impacts. © 2024 Elsevier B.V.

2024

Meta-learning and Data Augmentation for Stress Testing Forecasting Models

Authors
Inácio, R; Cerqueira, V; Barandas, M; Soares, C;

Publication
CoRR

Abstract

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