Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis

Reis-Marques, C., Figueiredo, R., & Neto, M. D. C. (2021). Applications of Blockchain Technology to Higher Education Arena: A Bibliometric Analysis. European Journal of Investigation in Health, Psychology and Education, 11(4), 1406-1421. https://doi.org/10.3390/ejihpe11040101 ---------------------------------------------- This work is financed by national funds through FCT—Fundação para a Ciência e a Tecnologia, I. P., under the project “UIDB/04630/2020”.Research related to blockchain is rapidly gaining importance in the higher education. This opportunity collaborates with a proposal for a review of papers on the main blockchain topic. The bibliometric analysis included 61 peer-reviewed articles published in the Scopus database during the period of 2016 to 2021. This paper offers the identification of gaps in the literature enabling studies on the subject in higher education. The article identifies the main applications of blockchain technology in higher education around the world, as well as suggests future investigations. For further scientific investigation, we propose the operationalization of each of the researched approaches, especially combining the blockchain relationship, artificial intelligence, digital innovation, digital maturity, and customer experience in higher education.publishersversionpublishe

Grand challenges in IoT and sensor networks

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HOW CAN EUROPEAN BLOCKCHAIN SERVICES INFRASTRUCTURE BE USED FOR MANAGING EDUCATIONAL DIGITAL CREDENTIALS?

Self-sovereign identity deals with the way individuals can manage their identity in the digital world. This is high in priority for European Blockchain Infrastructure (EBSI) that is leveraging blockchain technology and offers a decentralized solution that enables higher education institutions (HEI) to manage sensitive digital data that shouldn’t be forged, such as digital credentials (e.g., diplomas and proofs of studying). This simplifies the way digital credentials can be issued and verified by HEIs while giving the ownership of them to the learner. However, there is an absence of empirical research using EBSI ecosystem for cross-border verification of digital credentials. To address this gap, we used design science research method and developed an artefact. A study between two HEIs was conducted, and the artefact was evaluated through qualitative analysis by interviewing 19 administrators from HEIs. As a contribution, our study identifies 14 considerations that might affect the implementation of such a system in practice. However, we conclude that institutional and national strategies towards digital credentials play a bigger role than technical considerations for implementation

A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions

In recent decades, social network anonymization has become a crucial research field due to its pivotal role in preserving users' privacy. However, the high diversity of approaches introduced in relevant studies poses a challenge to gaining a profound understanding of the field. In response to this, the current study presents an exhaustive and well-structured bibliometric analysis of the social network anonymization field. To begin our research, related studies from the period of 2007-2022 were collected from the Scopus Database then pre-processed. Following this, the VOSviewer was used to visualize the network of authors' keywords. Subsequently, extensive statistical and network analyses were performed to identify the most prominent keywords and trending topics. Additionally, the application of co-word analysis through SciMAT and the Alluvial diagram allowed us to explore the themes of social network anonymization and scrutinize their evolution over time. These analyses culminated in an innovative taxonomy of the existing approaches and anticipation of potential trends in this domain. To the best of our knowledge, this is the first bibliometric analysis in the social network anonymization field, which offers a deeper understanding of the current state and an insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure

Security Engineering of Patient-Centered Health Care Information Systems in Peer-to-Peer Environments: Systematic Review

Background: Patient-centered health care information systems (PHSs) enable patients to take control and become knowledgeable about their own health, preferably in a secure environment. Current and emerging PHSs use either a centralized database, peer-to-peer (P2P) technology, or distributed ledger technology for PHS deployment. The evolving COVID-19 decentralized Bluetooth-based tracing systems are examples of disease-centric P2P PHSs. Although using P2P technology for the provision of PHSs can be flexible, scalable, resilient to a single point of failure, and inexpensive for patients, the use of health information on P2P networks poses major security issues as users must manage information security largely by themselves. Objective: This study aims to identify the inherent security issues for PHS deployment in P2P networks and how they can be overcome. In addition, this study reviews different P2P architectures and proposes a suitable architecture for P2P PHS deployment. Methods: A systematic literature review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. Thematic analysis was used for data analysis. We searched the following databases: IEEE Digital Library, PubMed, Science Direct, ACM Digital Library, Scopus, and Semantic Scholar. The search was conducted on articles published between 2008 and 2020. The Common Vulnerability Scoring System was used as a guide for rating security issues. Results: Our findings are consolidated into 8 key security issues associated with PHS implementation and deployment on P2P networks and 7 factors promoting them. Moreover, we propose a suitable architecture for P2P PHSs and guidelines for the provision of PHSs while maintaining information security. Conclusions: Despite the clear advantages of P2P PHSs, the absence of centralized controls and inconsistent views of the network on some P2P systems have profound adverse impacts in terms of security. The security issues identified in this study need to be addressed to increase patients\u27 intention to use PHSs on P2P networks by making them safe to use

PRIVAFRAME: A Frame-Based Knowledge Graph for Sensitive Personal Data

The pervasiveness of dialogue systems and virtual conversation applications raises an important theme: the potential of sharing sensitive information, and the consequent need for protection. To guarantee the subject’s right to privacy, and avoid the leakage of private content, it is important to treat sensitive information. However, any treatment requires firstly to identify sensitive text, and appropriate techniques to do it automatically. The Sensitive Information Detection (SID) task has been explored in the literature in different domains and languages, but there is no common benchmark. Current approaches are mostly based on artificial neural networks (ANN) or transformers based on them. Our research focuses on identifying categories of personal data in informal English sentences, by adopting a new logical-symbolic approach, and eventually hybridising it with ANN models. We present a frame-based knowledge graph built for personal data categories defined in the Data Privacy Vocabulary (DPV). The knowledge graph is designed through the logical composition of already existing frames, and has been evaluated as background knowledge for a SID system against a labeled sensitive information dataset. The accuracy of PRIVAFRAME reached 78%. By comparison, a transformer-based model achieved 12% lower performance on the same dataset. The top-down logical-symbolic frame-based model allows a granular analysis, and does not require a training dataset. These advantages lead us to use it as a layer in a hybrid model, where the logical SID is combined with an ANNs SID tested in a previous study by the authors

Re-Platformed Planet? The Rise and Spread of Chinese Technology Platform Companies

This thesis seeks to answer the question—what are the implications if Chinese platform technology companies expand around the world? To answer this question the research assesses whether platforms have powers of influence; if Chinese platforms have such powers; if they do, are they using such powers on behalf of the Chinese Communist Party (CCP) outside of China; and what might accelerate or inhibit their global expansion. The research expands on and connects current scholarship in a number of fields, among them: geoeconomics, business, technology & media, influence operations, and political economy. Evidence from a wide range of scholarship, Chinese policy documents, media coverage, and interviews provides answers to these questions. Two frameworks were developed to help evaluate platform influence powers and actors. Findings: Platforms are designed as “architectures of influence,” enabling a core set of actors to exert influence through them. Chinese platforms, have arguably enhanced influence capabilities because of their partnership in building and implementing China’s domestic surveillance and control infrastructure. Where they are expanding globally, there is evidence Chinese platforms are exerting influence on behalf of the CCP—and they are expanding rapidly, particularly in emerging markets. Nevertheless, they have not as yet superseded Western platforms’ presence. However, a number of factors could accelerate Chinese platform proliferation—innovation, loss of confidence in Western models, technology decoupling, internet standards and governance, and China’s technology stack. Other factors could inhibit their expansion—the current regulatory crackdown in China, impressions of China’s domestic and foreign policy actions, weaknesses in China’s soft power, and principal/agent effects. Based on the research and current trends, it is likely that Chinese platforms will continue to expand and act even more effectively on behalf of the CCP. The implications of this could be significant at the country level and for the global order. The thesis concludes with policy recommendations and suggested areas of further research

Intelligent Biosignal Analysis Methods

This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others