| Title | Resilience Estimation of Cyber-Physical Systems via Quantitative Metrics |
| Publication Type | Journal Article |
| Year of Publication | 2021 |
| Authors | Barbeau, Michel, Cuppens, Frédéric, Cuppens, Nora, Dagnas, Romain, Garcia-Alfaro, Joaquin |
| Journal | IEEE Access |
| Volume | 9 |
| Pagination | 46462–46475 |
| ISSN | 2169-3536 |
| Keywords | Attack Remediation, Biomedical monitoring, control theory, covert attacks, CPS Resilience, cps resiliency, Cyber-physical systems, Cyber-Resilience, Liquids, Mathematical model, Measurement, Monitoring, pubcrawl, Recoverability, resilience, resilience estimation, security metrics, Sensors |
| Abstract | This paper is about the estimation of the cyber-resilience of CPS. We define two new resilience estimation metrics: k-steerability and l-monitorability. They aim at assisting designers to evaluate and increase the cyber-resilience of CPS when facing stealthy attacks. The k-steerability metric reflects the ability of a controller to act on individual plant state variables when, at least, k different groups of functionally diverse input signals may be processed. The l-monitorability metric indicates the ability of a controller to monitor individual plant state variables with l different groups of functionally diverse outputs. Paired together, the metrics lead to CPS reaching (k,l)-resilience. When k and l are both greater than one, a CPS can absorb and adapt to control-theoretic attacks manipulating input and output signals. We also relate the parameters k and l to the recoverability of a system. We define recoverability strategies to mitigate the impact of perpetrated attacks. We show that the values of k and l can be augmented by combining redundancy and diversity in hardware and software, in order to apply the moving target paradigm. We validate the approach via simulation and numeric results. |
| Notes | Conference Name: IEEE Access |
| DOI | 10.1109/ACCESS.2021.3066108 |
| Citation Key | barbeau_resilience_2021 |
Resilience Estimation of Cyber-Physical Systems via Quantitative Metrics