Risk Assessment and Monitoring in Intelligent Data-Centric Systems

Abstract The cloud era is accelerating the long term growth of Data-Centric Systems in critical applications. In this chapter, we focus on the risk assessment methods of traditional large-scale, computer-based systems and on the necessity to extend such approaches to Data-Centric Systems. Hence, after a presentation of the main risk factors in traditional and future systems, an assessment methodology is presented showing how to use advanced formal modeling techniques as the multiformalism approach to evaluate security risk, based on two widespread formalisms: Bayesian Networks and Attack Trees.