An Approach for Dynamic Behavioural Prediction and Fault Injection in Cyber-Physical Systems

Hayatullahi Adeyemo, Rami Bahsoon, Peter Tino

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationBDCAT '23
Subtitle of host publicationProceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
ISBN (Print)9798400704734
DOIs
Publication statusPublished - 3 Apr 2024
EventBDCAT '23: IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies - Taormina (Messina), Italy
Duration: 4 Dec 20237 Dec 2023

Conference

ConferenceBDCAT '23
Country/TerritoryItaly
CityTaormina (Messina)
Period4/12/237/12/23

Keywords

  • Cyber-Physical System
  • Fault
  • Modelling
  • Dynamic Behavioural Prediction
  • Fault Injection

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