Abstract
This systematic literature review investigates the factors influencing cloud computing adoption within both educational and organizational settings. By synthesizing a comprehensive body of research, this study finds and analyzes the determinants that shape the decision-making process about cloud technology adoption. Security, cost-effectiveness, scalability, interoperability, and regulatory compliance are examined across educational institutions and organizational contexts. Additionally, socio-economic, political, and technological factors specific to each context are explored to provide a nuanced understanding of the challenges and opportunities associated with cloud computing adoption. The review reveals commonalities and differences in adoption drivers and barriers between education and organizational environments, offering insights into tailored strategies for effective implementation. This research contributes to the existing literature by shedding light on the multifaceted nature of cloud adoption and offering valuable guidance for educators, organizational leaders, policymakers, and technology providers looking to use cloud computing to enhance operations and services.

Abstract
Knowledge of Social Engineering is crucial to prevent potential attacks related to organizational Information Security. The objective of this paper aims to identify the most common social engineering techniques, success attack factors, and obstacles, as well as the good practices and frameworks that could be adopted concerning their mitigation. As an analysis methodology, a Systematic Literature Review was carried out. The findings revealed that the discussion about SE attacks has increased and that the most imminent threat is phishing. Exploiting human vulnerabilities is a growing threat when the attack is not carried out directly through technical means. There continue to be more technical attacks than non-technical attacks. Encouraging organizational security prevention, like training, education, technical controls, process development, defense in detail, and the development of security policies, should be considered mitigating factors for the negative impact of SE attacks. Most SE frameworks/models are focused on attack techniques and methods, mostly on technical components, decorating human factor. As a novelty, we found the opportunity to develop a new framework that could improve coverage of the gaps found, supported on security international standards, that could help and support researchers in developing their work, understanding open research topics, and providing a clearer understanding of this type of threat. © 2024 by the authors. Licensee ESJ, Italy.

Abstract
Cybercrime is growing rapidly, and it is increasingly important to use advanced tools to combat it and support investigations. One of the battlefronts is the forensic investigation of mobile devices to analyze their misuse and recover information. Mobile devices present numerous challenges, including a rapidly changing environment, increasing diversity, and integration with the cloud/IoT. Therefore, it is essential to have a secure and reliable toolbox that allows an investigator to thwart, discover, and solve all problems related to mobile forensics while deciphering investigations, whether criminal, civil, corporate, or other. In this work, we propose an original and innovative instantiation of a structure in a forensic toolbox for mobile devices, corresponding to a set of different applications, methods, and best practice information aimed at improving and perfecting the investigative process of a digital investigator. To ensure scientific support for the construction of the toolbox, the Design Science Research (DSR) methodology was applied, which seeks to create new and unique artifacts, drawing on the strength and knowledge of science and context. The toolbox will help the forensic investigator overcome some of the challenges related to mobile devices, namely the lack of guidance, documentation, knowledge, and the ability to keep up with the fast-paced environment that characterizes the mobile industry and market. © 2024 by the authors. Licensee ESJ, Italy.

Abstract
Enterprise Architecture (EA) is a coherent set of principles, methods, and models that express the structure and behavior of an enterprise and its IT landscape. EA mining uses data mining techniques to automate EA models’ extraction. Ontologies help to define concepts and the relationships among these concepts to describe a domain of interest. This paper presents an extensible ontology for EA mining to extract models using Application Program Interface (API) log files as the data source. The ontology development follows the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) and uses OntoUML 2.0 language to ensure its expressiveness and readability. To validate its theoretical feasibility and contribution to EA modeling, it presents a simulation of the ontology application through a controlled scenario using data structures similar to an industrial case. Then, the ontology is verified and validated, checking quality ontology criteria using specialized tools for syntactic and semantic model checking, which also aids in avoiding ontology anti-patterns. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
This research explores the adoption of ISO 20022, a standard that corporations can leverage to instruct payments to their partner financial institutions. Due to the complexity and case-specific variables involved, the adoption process may be complex and require significant effort from financial institutions and customers over an extended period. This research analyzes the opportunities and challenges for corporate users posed by ISO 20022 and identifies the success factors that must be considered during the adoption process. The research key findings indicate that an implementation approach incorporating flexibility, custom extensions, the use of a markup language for creating and managing messages, pilot testing, and user feedback can be an effective adoption model for ISO 20022. Design Science Research Methodology is employed in designing, building, and evaluating a solution proposal to develop a structured, customized, and flexible solution complying with the ever-changing requirements and landscape. This research contributes to the payment processing field by providing a comprehensive adoption model for ISO 20022 that considers critical factors and challenges. The proposed customized and flexible solution can assist corporations in successfully adopting ISO 20022 and contribute to creating a common language and model for payment data worldwide. The initiative's success depends on the effective adoption by all players, including corporations. © 2024 by the authors.

Abstract
Enterprise Architecture (EA) is defined as a set of principles, methods, and models that support the design of organizational structures, expressing the different concerns of a company and its IT landscape, including processes, services, applications, and data. One role of EA management is to automate modeling tasks and maintain up-to-date EA models while reality changes. However, EA modeling still relies primarily on manual methods. Contributing to EA modeling automation, EA Mining is an approach that uses data mining techniques for EA modeling and management. It automatically captures existing information in operational databases to generate architectural models and views. This paper presents an ontology for EA Mining that focuses on generating architectural models from API gateway log files. An ontology defines the concepts and relationships among them to uniquely describe a domain of interest and specify the meaning of the terms. API Gateways are information technology components that serve as a facade between information systems and enterprise business partners. The ontology development methodology followed the SABiO process, whereas the Unified Foundational Ontology provided the foundations of the ontology and OntoUML, the ontology modeling language. An experiment in an e-commerce application scenario was conducted to evaluate the theoretical feasibility and applicability of the ontology. Automatic semantic and syntactic validation tools and semi-structured expert interviews were used to confirm the desired ontology properties. This study aims to contribute to the evolution of the knowledge base of EA Management.