Conference Agenda

Current cybersecurity education is largely oriented toward tool-based training and vendor-dependent platforms, which often limits the development of ethical judgment, technological autonomy, and critical thinking in future professionals. This paper analyzes the importance of teaching Free Software as a formative foundation for Ethical Hacking and Cybersecurity education, emphasizing the distinction between technical training and integral professional formation. Based on sustained teaching experience in Cybersecurity Engineering, Information Security, Networks, and Artificial Intelligence programs, a conceptual educational model is proposed that integrates ethical, philosophical, and technical dimensions of Free Software into cybersecurity curricula. The approach highlights key elements such as access to source code, licensing awareness, transparency, and hacker culture as ethical practice. The main contribution of this work is a formative framework that strengthens professional criteria, responsible decision-making, and long-term adaptability, moving beyond a purely pragmatic use of tools toward an ethical and sustainable cybersecurity education model.

This article is based on the analysis of information and communication technologies that are used for the issue of public safety despite the fact that there are systems that have provided a contribution to the community selected by these researchers, the truth is that there may be a defect or flaw that may present this application for certain cases, this research aims to conduct a literature review on the use of these technologies under the theme of public safety in which, it was taken into account an investigation of a web system, two based on the development of a mobile application and two hybrid systems in which an analysis was made on the purpose of the research, a brief description of the developed system, the conclusion that these researchers reached and the respective observation on what deficiencies were found in these software’s, so that, within the information collected, it was found that both the web system and one of the hybrid systems denoted certain deficiencies regarding the low visibility of the entire system and the reduced efficiency of the system with respect to responses obtained from users regarding the operation of such software.

The expansion of digital technologies in criminal investigations has reshaped evidentiary practices and institutional decision-making in Latin America. Although digital evidence is often treated as neutral and inherently reliable, its evaluation involves technical opacity, epistemic asymmetries, and discretionary institutional decisions that could directly affect due process guarantees and, with them, human rights. This paper proposes a decision-making framework for the governance of evidence in general and digital evidence in particular, grounded in probative rationality and criminal policy analysis. Based on a qualitative examination of the practices of the Public Prosecutor’s Office in Northern Patagonia (Argentina), the study identifies structural risks associated with the uncritical use of technological evidence, including automation bias and early-stage over-criminalization. The proposed framework integrates normative, technical, and institutional dimensions to guide decision-making in preliminary phases of criminal investigations, offering a model transferable to Latin American justice systems.

Phishing through email is a growing threat to corporate cybersecurity, where traditional detection methods frequently fail against sophisticated attacks. This review aims to identify and evaluate automatic phishing detection methods (based on Deep Learning and Machine Learning) in contrast with traditional systems, focusing on email analysis and their application in corporate and organizational environments. Method: The review was structured using the PICOC methodology to formulate the research question. A systematic process based on PRISMA was applied, conducting searches in key databases such as Scopus and Web of Science. Articles published between 2021 and 2025 were selected, and after applying inclusion/exclusion criteria, 21 studies were thoroughly reviewed. Results: The findings demonstrate the algorithmic superiority of advanced methods, such as Deep Learning (DL) models and Transformer-based approaches (LLMs), which outperform traditional and shallow ML techniques. These models consistently achieved accuracies above 99% in classification tasks. Conclusions: The study identifies a critical operational gap: this high accuracy is limited to simulated environments and lacks evidence of validation in real corporate settings, such as Office 365. It is concluded that the practical applicability of the most accurate methods remains uncertain, requiring future research to focus on validation in production environments and on mitigating the risk of secondary threats such as ransomware.

Digitalization has propelled the financial sector at breakneck speed, multiplying transactions with the same ease with which fraud and cyberattacks also proliferate. It's almost ironic: while banks boast of two-step authentication and "unbreakable" encryption, cybercriminals seem to advance with the elegance of those who are always one step ahead. In this interplay of light and shadow, blockchain emerges, transparent as crystal and stubborn as an age-old law. The systematic review conducted of 62 studies published between 2021 and 2025, filtered using the PRISMA method from Scopus paints a promising picture: an 80% reduction in settlement times, optimized traceability, and up to 40% less risk of fraud. But it's not all technological triumph. Obstacles persist, as heavy as old inherited furniture: outdated infrastructure, doubts about scalability, and regulations that move with the slowness of a bureaucratic winter. Will blockchain be the future of financial security, or just a promise that shines more in theory than in practice? Time, that relentless auditor, will have the final say.

The widespread adoption of cloud computing has increased critical cyber threats, making it urgent to evaluate the effectiveness of conventional defense mechanisms. The objective of this research was to comparatively analyze modern cybersecurity strategies versus traditional methods in cloud environments. A systematic review was conducted under the PRISMA protocol, analyzing 65 articles from the Scopus database published between 2021 and 2025. The results reveal a technological transition where, although cryptography remains the predominant strategy in 49% of the studies, there is an accelerated growth of 38% in the adoption of Artificial Intelligence for proactive detection. It was also identified that unauthorized access and denial-of-service attacks continue to be the main threats. It is concluded that there is a methodological bias in the literature, which prioritizes efficiency metrics in simulations over real security validation; therefore, it is recommended to migrate to hybrid architectures validated in real operational scenarios to ensure information integrity.