A graph theory based generic risk assessment framework for internet of things (IoT)

Rapid deployment of Internet of Things (IoT) systems around the digital world is posing greater risks in terms of security and privacy. For IoT, risk assessment is complex due to its vast deployment and diversity (in terms of communication protocols, devices, environment, etc.). Thus traditional risk assessment frameworks do not effectively address all the risk assessment needs of IoT and hence there is a need for composing several such risk assessment frameworks. To address these issues, a model-driven risk assessment framework based on graph theory is proposed in this paper. Further, in the existing frameworks, end-to-end attack propagation is not addressed systematically. Hence, using bipartite graph technique, risk assessment through attack propagation is envisaged. The proposed framework is validated through empirical analysis and experiments.