Abstract
Modern technology integrates Cyber-Physical Systems (CPS), merging computational and physical processes. Ensuring CPS dependability is vital in averting adverse effects on critical applications due to unforeseen behaviour. To fortify CPS resilience, a novel technique for dynamic behavioural prediction and fault injection is introduced. It predicts dynamic CPS behaviour through system modelling under diverse operational scenarios, employing a fault model with diverse fault classes. Unlike the single model tenet, this approach engages multiple expert models to simulate both faultless and faulty behaviours. By adopting this approach, we can inject specialised faults and scale the analysis of the faults together or separately. Injecting faults assesses system reactions and reveals vulnerabilities. Tested on a water tank system, the approach proves effective in behaviour prediction and proactive fault handling, enhancing CPS design for robust, secure, and fault-tolerant systems.
Original language | English |
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Title of host publication | BDCAT '23 |
Subtitle of host publication | Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies |
Publisher | Association for Computing Machinery (ACM) |
Number of pages | 6 |
ISBN (Print) | 9798400704734 |
DOIs | |
Publication status | Published - 3 Apr 2024 |
Event | BDCAT '23: IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies - Taormina (Messina), Italy Duration: 4 Dec 2023 → 7 Dec 2023 |
Conference
Conference | BDCAT '23 |
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Country/Territory | Italy |
City | Taormina (Messina) |
Period | 4/12/23 → 7/12/23 |
Keywords
- Cyber-Physical System
- Fault
- Modelling
- Dynamic Behavioural Prediction
- Fault Injection