REVIEW 1 cited by
Quantitative Measurement of Cyber Resilience: Modeling and Experimentation
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original 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.
Forward citations
Cited by 1 Pith paper
-
Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence
In a two-objective CybORG defence game, MOPPO produced policies that trade off network defence against user access, while Pareto Conditioned Networks did not respond reliably to preference prompts.
Discussion (0). Continue with ORCID to comment.