http://repositorio.ufc.br/handle/riufc/69403 2026-06-08T09:52:37Z 2026-06-08T09:52:37Z Vasconcelos, Vitor Manuel Gomes http://repositorio.ufc.br/handle/riufc/86323 2026-05-15T20:21:28Z 2026-01-01T00:00:00Z

Título: Explorando abordagens de segurança para detecção de intrusão utilizando aprendizado de máquina em internet das coisas Autor(es): Vasconcelos, Vitor Manuel Gomes Abstract: The present work aims to analyze the use of state-of-the-art methods that involve Machine Learning (ML) techniques for defending against intrusion attacks in Internet of Things (IoT) networks. The study seeks to understand how research addressing defense mechanisms against intrusion attacks has evolved, selecting studies that focus on the use of ML as a protection approach, as well as identifying the main types of attacks and their motivations aimed at compromising IoT networks. Based on the selected articles, it was observed how defense applications employing ML techniques are applied, through the use of four data mining methods: analysis of the frequency of specific terms; the Apriori method for item frequency analysis; the clustering method for identifying groups with similar characteristics; and time series analysis to observe the behavior of the analyzed articles over the defined research period. In this way, it was possible to formulate three research questions addressing the challenges identified in this domain and how they may be mitigated through the use of ML in defending against intrusion attacks in IoT networks. Tipo: TCC

2026-01-01T00:00:00Z Andrade, Antônio Fábio Brandão de http://repositorio.ufc.br/handle/riufc/86322 2026-05-15T20:02:03Z 2025-01-01T00:00:00Z

Título: Utilização e Comparação dos Métodos Eigenfaces, Fisherfaces e LBPH no Processo de Reconhecimento Facial Autor(es): Andrade, Antônio Fábio Brandão de Abstract: Digital security has become an increasingly relevant topic in light of technological advancements and the rise of cyber threats. In this context, facial recognition emerges as a promising solution for authentication and access control. This work presents a comparison between the Eigenfaces, Fisherfaces, and Local Binary Patterns Histograms (LBPH) methods for facial recognition. The study is justified by the growing demand for accurate and efficient facial identification methods in contexts requiring high levels of access control and information protection. Initially, the theoretical foundations related to computer vision, face detection, and facial recognition are explored. In the methodological process, the algorithms are implemented using the OpenCV library in Python. The image acquisition phase is carried out using two datasets: one created by the author and another obtained from the internet. The image preprocessing stage includes conversion to grayscale, resizing, and the application of filters. This step is crucial, as it provides the necessary foundation for the subsequent stages of face detection and recognition. The algorithms are evaluated in terms of accuracy, precision, recall, and F1-score. The results indicate that the LBPH algorithm demonstrates the best overall performance, with an accuracy of 98%, followed by Fisherfaces with 92%, and Eigenfaces with 88%. Additionally, the main advantages and limitations of each algorithm are discussed. This study contributes to a comparative understanding of facial recognition methods and provides a valuable reference for selecting the most suitable algorithm for access control systems in indoor environments. Tipo: TCC

2025-01-01T00:00:00Z Matos, Aryely Maria Silva http://repositorio.ufc.br/handle/riufc/86135 2026-05-06T00:30:16Z 2025-01-01T00:00:00Z

Título: Privacidade de Dados na Prática de Software: Perspectivas de Desenvolvedores Brasileiros Autor(es): Matos, Aryely Maria Silva Abstract: Data privacy is an essential principle of information security, aimed at protecting sensitive data from unauthorized access and information leaks. As software systems advance, the volume of personal information also grows exponentially. Therefore, incorporating privacy engineering practices during development is vital to ensure data integrity, confidentiality, and compliance with legal regulations, such as the General Data Protection Law (LGPD). However, there is a gap in understanding developers’ awareness of data privacy, their perceptions of implementing privacy strategies, and the influence of organizational factors on this adoption. Thus, this paper aims to explore the level of awareness among Brazilian developers regarding data privacy and their perceptions of the implementation strategies adopted to ensure data privacy. Additionally, we seek to understand how organizational factors influence the adoption of data privacy practices. To this end, we surveyed 88 Brazilian developers with privacy-related work experience. We got 21 statements grouped into three topics to measure the Brazilian developers’ awareness of data privacy in software. Our statistical analysis reveals substantial gaps between groups, e.g., developers have Direct v.s. Indirect data privacy-related work experience. We also reveal some data privacy strategies, e.g., Encryption, are both widely used and perceived as highly important; others, such as turning off data collection, highlight strategies where ease of use does not necessarily lead to widespread adoption. Finally, we identified that the absence of dedicated privacy teams correlates with a lower perceived priority and less investment in tools. Even in organizations that recognize the importance of privacy. Our findings offer insights into how Brazilian developers perceive and implement data privacy practices, emphasizing the critical role organizational culture plays in decision-making regarding privacy. We hope that our findings will contribute to improving privacy practices within the software development community, particularly in contexts similar to Brazil. Tipo: TCC

2025-01-01T00:00:00Z Bastos, Carlos Adriel Sousa http://repositorio.ufc.br/handle/riufc/86134 2026-05-06T00:26:04Z 2026-01-01T00:00:00Z

Título: Caracterização de Práticas de AppSec e da Adoção de Ferramentas Automatizadas de Segurança: Um Questionário Abrangente com Desenvolvedores Brasileiros Autor(es): Bastos, Carlos Adriel Sousa Abstract: The adoption of Application Security (AppSec) practices is essential to protect software systems against vulnerabilities and cyber threats. However, the effectiveness of these practices strongly depends on their consistent adoption and on developers’ perceptions regarding their ease of use, perceived effectiveness, essentiality, and applicability within the software development context. This study aims to characterize a set of AppSec practices in terms of frequency of use, ease of application, perceived effectiveness, and perceived essentiality in software development. In addition, it seeks to analyze how automated security tools are being incorporated into the development process and to identify the main challenges faced by Brazilian developers in their adoption. To achieve these objectives, we first conducted a survey of related work in the scientific literature, from which an initial and comprehensive set of software security practices was identified and cataloged. This initial set then underwent an iterative process of filtering, refinement, and grouping, carried out by experts in Software Engineering and Software Security, intending to reduce redundancy, harmonize terminology, and ensure both conceptual and practical relevance. As a result, a final set of 16 AppSec practices was defined. Subsequently, a questionnaire was designed and administered to software developers working in Brazil, yielding a total of 83 valid participants. The questionnaire collected information about participants’ profiles, their experience with software security, their adoption and perceptions of AppSec practices, and their use of automated security tools. The results reveal a heterogeneous landscape of AppSec practice adoption, with significant variations across practices in terms of frequency of use, ease of application, perceived effectiveness, and perceived essentiality. Practices such as code review and the use of static analysis tools show widespread adoption, whereas others, such as threat modeling and penetration testing, exhibit lower applicability. Moreover, although automated security tools are widely perceived as valuable, developers report recurring challenges related to learning curves, false positives, and integration into existing development workflows. The findings contribute to a deeper understanding of the actual use of security practices and tools in software development within the Brazilian context. The results are expected to inform educational initiatives and organizational strategies aimed at strengthening developers’ security culture and promoting a more consistent and effective adoption of AppSec practices. Tipo: TCC

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