2021
Autores
Araújo, R; Pinto, A;
Publicação
J. Cybersecur. Priv.
Abstract
2021
Autores
Araújo, R; Pinto, A; Pinto, P;
Publicação
ICT Systems Security and Privacy Protection - 36th IFIP TC 11 International Conference, SEC 2021, Oslo, Norway, June 22-24, 2021, Proceedings
Abstract
Vulnerability scanning tools can help secure the computer networks of organisations. Triggered by the release of the Tsunami vulnerability scanner by Google, the authors analysed and compared the commonly used, free-to-use vulnerability scanners. The performance, accuracy and precision of these scanners are quite disparate and vary accordingly to the target systems. The computational, memory and network resources required be these scanners also differ. We present a recent and detailed comparison of such tools that are available for use by organisations with lower resources such as small and medium-sized enterprises. © 2021, IFIP International Federation for Information Processing.
2021
Autores
Fernandes, R; Pinto, P; Pinto, A;
Publicação
2021 IEEE INTERNATIONAL MEDITERRANEAN CONFERENCE ON COMMUNICATIONS AND NETWORKING (IEEE MEDITCOM 2021)
Abstract
The Malware Information Sharing Platform (MISP) enables the sharing of cyberthreat information within a community, company or organisation. However, this platform presents limitations if its information is deemed as classified or shared only for a given period of time. This implies that this information should to be handled only in encrypted form. One solution is to use MISP with searchable encryption techniques to impose greater control over the sharing of information. In this paper, we propose a controlled information sharing functionality that features a synchronisation procedure that enables classified data exchange between MISP instances, based on policies and ensuring the required confidentiality and integrity of the shared data. Sequence charts are presented validating the configuration, the data synchronisation, and the data searching between multiple entities.
2021
Autores
Gonçalves, R; Ferreira, I; Godina, R; Pinto, P; Pinto, A;
Publicação
Blockchain and Applications - 3rd International Congress, BLOCKCHAIN 2021, Salamanca, Spain, 6-8 October, 2021
Abstract
2021
Autores
Pinto, A; Correia, A; Alves, R; Matos, P; Ascensão, J; Camelo, D;
Publicação
Wireless Mobile Communication and Healthcare - 10th EAI International Conference, MobiHealth 2021, Virtual Event, November 13-14, 2021, Proceedings
Abstract
For the regularly medicated population, the management of the posology is of utmost importance. With increasing average life expectancy, people tend to become older and more likely to have chronic medical disorders, consequently taking more medicines. This is predominant in the older population, but it’s not exclusive to this generation. It’s a common problem for all those suffering from chronic diseases, regardless of age group. Performing a correct management of the medicines stock, as well as, taking them at the ideal time, is not always easy and, in some cases, the diversity of medicines needed to treat a particular medical disorder is a proof of that. Knowing what to take, how much to take, and ensuring compliance with the medication intervals, for each medication in use, becomes a serious problem for those who experience this reality. The situation is aggravated when the posology admits variable amounts, intervals, and combinations depending on the patient’s health condition. This paper presents a solution that optimizes the management of medication of users who use the services of institutions that provide health care to the elderly (e.g., day care centers or nursing homes). Making use of the NB-IoT network, artificial intelligence algorithms, a set of sensors and an Arduino MKR NB 1500, this solution, in addition to the functionalities already described, eHealthCare also has mechanisms that allow identifying the non-adherence to medication by the elderly. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
2021
Autores
Guimaraes, N; Figueira, A; Torgo, L;
Publicação
PROCEEDINGS OF 2021 16TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2021)
Abstract
Twitter has become a major platform to share ideas and promoting discussion on relevant topics. However, with a large number of users to resort to it as their primary source of information and with an increasing number of accounts spreading newsworthy content, a characterization of the political bias associated with the social network ecosystem becomes necessary. In this work, we aim at analyzing accounts spreading or publishing content from five different classes of the political spectrum. We also look further and study accounts who spread content from both right and left sides. Conclusions show that there is a large presence of accounts which disseminate right bias content although it is the more central classes that have a higher influence on the network. In addition, users who spread content from both sides are more actively spreading right content with opposite content associated with criticism towards left political parties or promoting right political decisions.
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