Visible to the public Modelling Adversarial Flow in Software-Defined Industrial Control Networks Using a Queueing Network Model

TitleModelling Adversarial Flow in Software-Defined Industrial Control Networks Using a Queueing Network Model
Publication TypeConference Paper
Year of Publication2020
AuthorsNweke, Livinus Obiora, Wolthusen, Stephen D.
Conference Name2020 IEEE Conference on Communications and Network Security (CNS)
Date PublishedJune 2020
ISBN Number978-1-7281-4760-4
KeywordsAdversarial flow, Analytical models, composability, Computer architecture, control theory, industrial control systems, process control, pubcrawl, QoS, quality of service, Queueing analysis, Queueing network model, resilience, Resiliency, SDN, security, Software
AbstractIn recent years, software defined networking (SDN) has been proposed for enhancing the security of industrial control networks. However, its ability to guarantee the quality of service (QoS) requirements of such networks in the presence of adversarial flow still needs to be investigated. Queueing theory and particularly queueing network models have long been employed to study the performance and QoS characteristics of networks. The latter appears to be particularly suitable to capture the behaviour of SDN owing to the dependencies between layers, planes and components in an SDN architecture. Also, several authors have used queueing network models to study the behaviour of different application of SDN architectures, but none of the existing works have considered the strong periodic network traffic in software-defined industrial control networks. In this paper, we propose a queueing network model for softwaredefined industrial control networks, taking into account the strong periodic patterns of the network traffic in the data plane. We derive the performance measures for the analytical model and apply the queueing network model to study the effect of adversarial flow in software-defined industrial control networks.
Citation Keynweke_modelling_2020