ARES: Automated Risk Estimation in Smart Sensor Environments

Published

August 17, 2020

Author(s)

Athanasios Dimitriadis, Jose L. Flores, Boonserm Kulvatunyou, Nenad Ivezic, Ioannis Mavridis

Abstract

Industry 4.0 adoption demands integrability, interoperability, composability, and security. Currently, integrability, interoperability and composability are addressed by next-generation approaches for enterprise systems integration such as model-based standards, ontology, business process model life cycle management and the context of business processes. Security is addressed by conducting risk management as a first step. Nevertheless, security risks are very much influenced by the assets that the business processes are supported. To this end, this paper proposes an approach for automated risk estimation in smart sensor environments, called ARES, which integrates with the business process model life cycle management. To do so, ARES utilizes standards for platform, vulnerability, weakness, and attack pattern enumeration in conjunction with a well-known vulnerability scoring system. The applicability of ARES is demonstrated with an application example that concerns a typical case of a microSCADA controller and a prototype tool called Business Process Cataloging and Classification System. Moreover, a computer-aided procedure for mapping attack patterns-to-platforms is proposed, and evaluation results are discussed revealing few limitations.

Citation

Sensors

Volume

20

Issue

16

Pub Type

Journals

Download Paper

https://doi.org/10.3390/s20164617

Local Download

Keywords

smart sensor environments, information system risk assessment, business process context, Common Security Standards

Citation

Dimitriadis, A. , Flores, J. , Kulvatunyou, B. , Ivezic, N. and Mavridis, I. (2020), ARES: Automated Risk Estimation in Smart Sensor Environments, Sensors, [online], https://doi.org/10.3390/s20164617 (Accessed October 14, 2024)