ExSol

Author:

Lamp Josephine1,Rubio-Medrano Carlos E.2,Zhao Ziming3,Ahn Gail-Joon4

Affiliation:

1. University of Virginia, Virginia, USA

2. Texas A&M University–Corpus Christi, Corpus Christi, Texas, USA

3. The University at Buffalo, Buffalo, New York, USA

4. Arizona State University and Samsung Research, Tempe, Arizona, USA

Abstract

No longer just prophesied about, cyber-attacks to Energy Delivery Systems (EDS) (e.g., the power grid, gas and oil industries) are now very real dangers that result in non-trivial economical losses and inconveniences to modern societies. In such a context, risk analysis has been proposed as a valuable way to identify, analyze, and mitigate potential vulnerabilities, threats, and attack vectors. However, performing risk analysis for EDS is difficult due to their innate structural diversity and interdependencies, along with an always-increasing threatscape. Therefore, there is a need for a methodology to evaluate the current system state, identify vulnerabilities, and qualify risk at multiple granularities in a collaborative manner among different actors in the context of EDS. With this in mind, this article presents ExSol , a collaborative, real-time, risk assessment ecosystem that features an approach for modeling real-life EDS infrastructures, an ontology traversal technique that retrieves well-defined security requirements from well-reputed documents on cyber-protection for EDS infrastructures, as well as a methodology for calculating risk for a single asset and for an entire system. Moreover, we also provide experimental evidence involving a series of attack scenarios in both simulated and real-world EDS environments, which ultimately encourage the adoption of ExSol in practice.

Publisher

Association for Computing Machinery (ACM)

Subject

General Medicine

Reference24 articles.

1. Improving Resilience of Interdependent Critical Infrastructures via an On-Line Alerting System

2. Risk assessment for industrial control systems quantifying availability using mean failure cost (MFC);Chen Qian;Journal of Artificial Intelligence and Soft Computing Research,2015

3. Energy Sector Control Systems Working Group (ESCSWG). 2014. Cybersecurity Procurement Language for Energy Delivery Systems. https://www.energy.gov/ceser/downloads/cybersecurity-procurement-language-energy-deliveryapril-2014. Energy Sector Control Systems Working Group (ESCSWG). 2014. Cybersecurity Procurement Language for Energy Delivery Systems. https://www.energy.gov/ceser/downloads/cybersecurity-procurement-language-energy-deliveryapril-2014.

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