Complex systems: Risk model based on social network analysis

Risk is difficult to analyze and predict in complex systems, especially if it is necessary to evaluate mission-critical systems risks in real-time. This work proposes a theoretical model, based on social network analysis and risk classification. The work objective is to understand risks from data and evidence obtained in real time, not coming from statistics of similar systems nor risk probabilities taken a priori. The analysis model seeks to design the structure or environment at risk as a complex system in which all components and relations are essential. These components and their relations form a social network, which can be analysed through the mathematics of Graphs. This is the main point and the novelty of the work, which will allow users of the method to assess risks in real time. As an example to illustrate the model application a typical datacenter diagram is showed in the paper, and used as a complex system to perform a case study.