Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

TL;DR

This paper presents an experimental approach and mathematical models for quantitatively measuring cyber resilience in cyber-physical systems, demonstrated on an autonomous truck with cyber-defense features.

Contribution

It introduces a systematic experimental method and parsimonious models for quantifying cyber resilience in cyber-physical systems.

Findings

Identified quantitative resilience characteristics from experimental data.

Demonstrated the approach on an autonomous truck with cyber-defense.

Showed the models can effectively measure system resilience.

Abstract

Cyber resilience is the ability of a system to resist and recover from a cyber attack, thereby restoring the system's functionality. Effective design and development of a cyber resilient system requires experimental methods and tools for quantitative measuring of cyber resilience. This paper describes an experimental method and test bed for obtaining resilience-relevant data as a system (in our case -- a truck) traverses its route, in repeatable, systematic experiments. We model a truck equipped with an autonomous cyber-defense system and which also includes inherent physical resilience features. When attacked by malware, this ensemble of cyber-physical features (i.e., "bonware") strives to resist and recover from the performance degradation caused by the malware's attack. We propose parsimonious mathematical models to aid in quantifying systems' resilience to cyber attacks. Using the models, we identify quantitative characteristics obtainable from experimental data, and show that these characteristics can serve as useful quantitative measures of cyber resilience.