- By:
- ahmed mithu, M; Rogers, Mike; Ulybyshev, Denis; Manicavasagam, Rajesh; Asmar Awad, Rima L
- Page Number:
- 1-4
- Volume:
- 34
- Issue Number:
- 1
- Publication Date:
- March 12, 2026
- Conference Name:
- The Florida Artificial Intelligence Research Society
- Conference Location:
- North Miami Beach, Florida, United States of America
- Conference Sponsor:
- FloridaOJ
- View DOI Listing:
- https://doi.org/10.32473/flairs.v34i1.128626
Abstract
Control systems are used to automate industrial processes, smart grids, and smart cities. Unfortunately, cyber attacks on control systems are on the rise. Additionally, control systems lack the plethora of tools available for commodity systems for forensic investigation. An important step towards the proper forensic investigation is to analyze device memory. To assist in identifying features of device memory, we present a machine learning-based technique that integrates ontology information for feature classification in a control system device’s memory.
