Management of information security indicators under a cognitive security model

Organizations face daily different computer security threats, which makes necessary to have a Decision Support System (DSS) that allows generating knowledge to define strategies to minimize risk. The information security management supported in DSS requires time-consuming manual processes, analysis of large amounts of data and the experience of security specialists. The use of alternatives such as bigdata, machine learning, data analytics, and data visualization can reduce the time of manual processes and the automation of data analysis, contributing the inclusion of intelligence to decision support systems. This study presents a conceptual framework based on the three components of information security: people, technology and processes, with a cognitive approach; emphasizing the aspect of technology in the management of indicators through the integration of concepts such as bigdata, machine learning, data analytics, and data visualization to strengthen the DSS for the generation of knowledge and to help security specialists to make decisions at a strategic level.