Data · dataset · 2025
Cyber-Physical Multi-Agent Systems
Listed in Teesside University Research Data Repository
This study is based on the hypothesis that an observer-based event-triggered consensus control method can ensure secure and resilient consensus in nonlinear cyber-physical multi-agent systems (CPMASs), even under multiple randomly occurring cyber-attacks such as deception and Denial-of-Service (DoS) attacks.
Description
The dataset used in this research is generated from numerical simulations of a representative CPMAS model, characterized by a directed communication graph and subjected to randomly occurring cyber-attacks.
These attacks include both deception and DoS scenarios, designed to emulate realistic and unpredictable network vulnerabilities in cyber-physical infrastructures. Simulation data include time-series of agent state trajectories, triggering instants, control inputs, and attack indicators. All simulations were carried out in MATLAB/Simulink using the parameters and conditions specified in the manuscript.
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The data reflect both nominal system behavior and system performance under adversarial conditions. Notable findings demonstrate that the proposed control framework successfully guarantees resilient consensus and exponential mean-square stability of the CPMASs, even in the presence of multiple attack types. Additionally, the event-triggered mechanism effectively reduces communication frequency between agents, optimizing resource utilization without compromising stability.
Links
Where it is published
- DOI doi.org/10.17632/gp5gd8svxs.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science
- Inferred from text
- Simulation 75%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/gp5gd8svxs.1 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |