ArticleSensors (Basel, Switzerland)2023
Security Analysis of Cyber-Physical Systems Using Reinforcement Learning.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Security Control of Cyber-Physical Systems under Cyber Attacks: A Survey.Sensors (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Future engineering systems with new capabilities that far exceed today's levels of autonomy, functionality, usability, dependability, and cyber security are predicted to be designed and developed using cyber-physical systems (CPSs). In this paper, the security of CPSs is investigated through a case study of a smart grid by using a reinforcement learning (RL) augmented attack graph to effectively highlight the subsystems' weaknesses. In particular, the state action reward state action (SARSA) RL technique is used, in which the agent is taken to be the attacker, and an attack graph created for the system is built to resemble the environment. SARSA uses rewards and penalties to identify the worst-case attack scenario; with the most cumulative reward, an attacker may carry out the most harm to the system with the fewest available actions. Results showed successfully the worst-case attack scenario with a total reward of 26.9 and identified the most severely damaged subsystems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.