Visible to the public Quantitative safety-security risk analysis of interconnected cyber-infrastructures

TitleQuantitative safety-security risk analysis of interconnected cyber-infrastructures
Publication TypeConference Paper
Year of Publication2022
AuthorsKumar, Rajesh
Conference Name2022 IEEE 10th Region 10 Humanitarian Technology Conference (R10-HTC)
KeywordsAnalytical models, attack-fault trees, Computer architecture, cyber risk assessment, Cybersecurity Damage Assessment, Measurement, pubcrawl, reliability, reliability block diagrams, resilience, Resiliency, Safety-security risk analysis, security, statistical analysis, Synchronization
AbstractModern 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.
DOI10.1109/R10-HTC54060.2022.9929906
Citation Keykumar_quantitative_2022