Biblio

Modern day cyber-infrastructures are critically dependent on each other to provide essential services. Current frameworks typically focus on the risk analysis of an isolated infrastructure. Evaluation of potential disruptions taking the heterogeneous cyber-infrastructures is vital to note the cascading disruption vectors and determine the appropriate interventions to limit the damaging impact. This paper presents a cyber-security risk assessment framework for the interconnected cyber-infrastructures. Our methodology is designed to be comprehensive in terms of accommodating accidental incidents and malicious cyber threats. Technically, we model the functional dependencies between the different architectures using reliability block diagrams (RBDs). RBDs are convenient, yet powerful graphical diagrams, which succinctly describe the functional dependence between the system components. The analysis begins by selecting a service from the many services that are outputted by the synchronized operation of the architectures whose disruption is deemed critical. For this service, we design an attack fault tree (AFT). AFT is a recent graphical formalism that combines the two popular formalisms of attack trees and fault trees. We quantify the attack-fault tree and compute the risk metrics - the probability of a disruption and the damaging impact. For this purpose, we utilize the open source ADTool. We show the efficacy of our framework with an example outage incident.

Risk assessment of cyber-physical systems, such as power plants, connected devices and IT-infrastructures has always been challenging: safety (i.e., absence of unintentional failures) and security (i. e., no disruptions due to attackers) are conditions that must be guaranteed. One of the traditional tools used to help considering these problems is attack trees, a tree-based formalism inspired by fault trees, a well-known formalism used in safety engineering. In this paper we define and implement the translation of attack-fault trees (AFTs) to a new extension of timed automata, called parametric weighted timed automata. This allows us to parametrize constants such as time and discrete costs in an AFT and then, using the model-checker IMITATOR, to compute the set of parameter values such that a successful attack is possible. Using the different sets of parameter values computed, different attack and fault scenarios can be deduced depending on the budget, time or computation power of the attacker, providing helpful data to select the most efficient counter-measure.