Metodología para la Investigación Forense en Entornos Cloud: Desafíos de Gobernanza y Niveles de Servicio en el Apoyo Institucional
The introduction to this article focuses on explaining the issues related to cloud forensic investigation in the context of digital governance and SLAs within institutional support, with an emphasis on cloud forensic methodologies. To this end, a qualitative literature review was conducted, drawing on documents, postgraduate theses, and academic articles available in databases. These types of documents were used to create files that facilitated data collection, allowing them to be sorted and compared with other sources. The lack of standards and interoperability between providers results in a significant number of problems in case law, as well as in the limited advancement of forensic investigation methodologies in the cloud. In addition to the above, they are also divided by multi-clouds. However, it is possible to observe a certain degree of progress in cloud forensic investigation, especially in Latin American legislation, which results in a lack of adequate legislation and institutional resources. The review indicates that the fusion between the technical, organizational, and legal components of digital forensic investigation must be improved, integrating criteria that ensure the integrity of evidence, procedural validity, and public confidence in digital justice systems. This study, in turn, enriches the academic and professional debate on the urgent need to design adaptive and standardized models that serve scientific research and institutional robustness in response to today's cybersecurity challenges.
Authors
- J. Torres (ORCID: https://orcid.org/0000-0003-1508-2371)
- Johemir Jesús Pérez Pertuz (ORCID: https://orcid.org/0000-0002-5094-0530)
- Juan Camilo Avila Moreno
Institutions
- Fundación Centro Tecnológico de la Información y la Comunicación (ES)
Publication Details
- Journal
- Ibero Ciencias - Revista Científica y Académica - ISSN 3072-7197
- Published
- 2025-09-16
- DOI
- https://doi.org/10.63371/ic.v4.n3.a272
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00