Abstraction of linked data’s world

Introduction: This article is the result of a research process whose product was to generate a guide for Higher Education Institutions (in Spanish, IES) to adopt a Cybersecurity Model based on ISO standards (International Organization for Standardization). Problem: IES do not have a cybersecurity model aligned to the ISO / IEC 27032: 2012 standard (International Organization for Standardization / International Electrotechnical Commission), which causes a lack of clarity and uncertainty in the level of maturity and low efficiency in processes and information security controls to be implemented. Objective: Propose a dynamic model of cybersecurity based on ISO standards for IES. Methodology: The development of this work was oriented under a line of applied research, by virtue of the fact that it was necessary to address the problem based on previous knowledge that allowed supporting the theoretical contributions and the activities proposed to determine the possible causes of the problem and give it a possible solution. Results: The generation of this dynamic model allows it to be adapted to the different needs and requirements of IES. Conclusion: IES can implement a cybersecurity model to prevent and protect information at the cyberspace level. Originality: The work carried out generates a great contribution, which is the generation of a dynamic cybersecurity model, since at present there are no specific models for IES. Limitations: The model implementation guide is established in a general way to be applied later to an organization in any sector. Keywords: Dynamic Cybersecurity Model, Higher Education Institutions, ISO/IEC 27032: 2012, Security Standards.

“…IES must have a cybersecurity model in place to prevent and protect information at the cyberspace level, [25], [26], [27].…”

Section: Discussionmentioning

confidence: 99%

Dynamic Cybersecurity Model based on ISO standards for Higher Education Institutions in Colombia

Taborda¹

2021

“…The constant change in the behavior of the actors belonging to the proposed model, makes the general behavior of the model similar to that of Complex Adaptive Systems (CAS) . In this way, it is proposed as future work, validating with real data, as it is a complex system with interconnected and adaptive actors , continuously improving according to globalization and the challenges that arise in society, [37], [38], [39].…”

Section: Discussionmentioning

confidence: 99%

Knowledge management model for decision-making through ontologies for an employment and employability observatory

Beltrán

Suarez²,

Nieto³

2021

Introduction: This article is the product of the research "Knowledge management model for decision-making through ontologies for an employment and employability observatory" developed within the ComplexUD Research Group in the Universidad Distrital Francisco José de Caldas between 2018 and 2020. Objective: The objective of this research is the construction of a knowledge management model using ontologies of the actors involved in the employability process. Methodology: The construction of knowledge was carried out through the creation of ontologies, which describe the conceptual components of each actor that participates in employability, since their interaction forms the proposed model. Conclusion: It is observed that representing the actors through ontologies allows the behavior among them to be modeled in a way that is very close to reality, however, it must be taken into account that the components that describe the actors can change over time, for what is necessary a periodic update of the model. Originality: This document proposes original ideas regarding the definition and behavior of the actors identified in the development of the research, if the work of other authors is mentioned throughout the article, it is cited according to the norms established by its publication.

“…The model of [20] and [21] is adapted to allow the development of simulations of a discrete environment and includes the following stages: i) System definition: characterize the internal and/or external interactions of the components of the simulation environment through an analysis that identifies the relationships, constraints and variables analyze the results in order to provide feedback to the environment and correct possible errors to obtain better results vii) Documentation: include a description of the processing and interpretation of the data and the environment developed, [32].…”

Section: Methodsmentioning

confidence: 99%

Performance of routing and spectrum allocation (RSA) algorithms for a last generation centralized optical network (SDON)

Ortega¹

2021