Learning Journey on Informatics 2024

Authors

Claudia Cappelli (ed)
UERJ
Eduardo Adilio Pelinson Alchieri (ed)
UnB

Keywords:

Decentralized Finance (DeFi) , Interoperability, Blockchain Networks , Security, Self-Supervised Learning, NoSQL, Differential Privacy, Social Networks

Synopsis

It is with pleasure that we present the 2024 edition of the book from the Learning Journey on Informatics series. The chapters in this book serve as supplementary material for the short courses selected to be presented at the Learning Journey on Informatics (JAI), traditionally held in conjunction with the Congress of the Brazilian Computing Society (SBC). The JAI is one of the most significant academic events for scientific and technological updates within the Brazilian computing community.

The JAI short courses cover current and relevant topics, are taught by experienced researchers, and provide an excellent opportunity for updating knowledge for academics and professionals in the field. This edition features 4 short courses presented during the SBC Congress. During the selection process, each proposal was reviewed by at least three evaluators, and the short course texts, which correspond to the chapters of this book, were reviewed by committee members to ensure their final quality.

Chapter 1 provides an in-depth discussion on three essential and driving aspects of the decentralized finance (DeFi) ecosystem: (1) innovative applications, (2) interoperability between blockchain networks, and (3) security for vulnerabilities in decentralized and competitive environments. In this context, the chapter also presents the fundamentals and practical examples of the most popular DeFi applications today, as well as discussing state-of-the-art research on the three aforementioned aspects that will support the growth of DeFi in the coming years.

Chapter 2 addresses and contextualizes self-supervised learning as an alternative for dynamic network applications, where data labeling is a critical challenge due to the discrepancy between traffic generation rates and manual data labeling rates. Generative and contrastive self-supervised learning techniques are presented for their effectiveness in improving network performance, expanding the number of labeled samples, and recognizing similarities and differences between sample examples. Finally, the chapter introduces self-supervised learning algorithms, their characteristics, and their applications in networks, aiming to equip readers with an understanding of the principles, frameworks, and limitations of this technique.

Chapter 3 presents the main concepts of NoSQL technology. Additionally, the chapter shows how to assess whether this technology is appropriate for the database design of a given system. The chapter also discusses some strategies for tuning the performance of NoSQL databases.

Chapter 4 provides an overview of differentially private methods and techniques to protect sensitive information while allowing relevant analysis of social networks. The principles of differential privacy are explored, highlighting mechanisms for adding noise to data to prevent individual reidentification. Additionally, strategies for applying differential privacy in social network data analysis are investigated, covering data publication, graph analysis, and machine learning tasks in a private manner.

We would like to thank the authors for submitting proposals and generating the final texts, and the Evaluation Committee for their dedication and efficiency throughout the short course selection process. Furthermore, we hope that all the material produced in this edition contributes to the education of students and professionals in the field.

Chapters

  • 1. Decentralized Finance on Blockchain Networks: Perspectives on Research and Innovation in Applications, Interoperability, and Security
    Josué N. Campos, Ronan D. Mendonça, Alexandre Fontinele, Luís H. S. de Carvalho, Isdael R. Oliveira, Ítallo W. F. Cardoso, Rafael Coelho, Allan E. S. Freitas, Glauber D. Gonçalves, José A. M. Nacif, Alex B. Vieira
  • 2. Generative and Contrastive Self-Supervised Learning: Trends and Challenges for Dynamic Network Applications
    João Vitor Valle Silva, Guilherme Nunes Nasseh Barbosa, Willian Tessaro Lunardi, Martin Andreoni, Diogo Menezes Ferrazani Mattos
  • 3. Design and Performance Tuning of NoSQL Databases
    Arlino Magalhães, Francisco Imperes, Manoel Melo
  • 4. Private Data Analysis in Social Networks
    André L. C. Mendonça, Felipe T. Brito, Javam C. Machado

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