Dissertation Proposal - Chibuzo Ukegbo

A Framework for Identification, Verification, and Validation of Safety and Security Properties of PLC Programs Using Cooperative and Ontology Verification Techniques

Presented by Chibuzo Ukegbo, Cybersecurity emphasis
Hybrid format: City Center Plaza Conference Room 352 or via Zoom

Abstract

The importance of ensuring PLC programs’ safety and security properties cannot be overstated. Considering that all the critical infrastructures—power grids, nuclear reactors, aviation, water treatment plants, etc.—are driven by PLCs, any violations of property specifications could lead to colossal damage to lives and equipment. Therefore, it calls for proper verification of PLC programs, identifying sources of vulnerabilities in the code by ensuring that the properties specified, and those not set are satisfied by the model of PLC programs. To this end, we propose a framework that uses cooperative verification, ontology, and machine learning techniques to verify, detect, and prevent PLC program violations and associated attacks, such as advanced persistent threats (APTs), both statically and dynamically. The cooperative approach involves the combination of verification tools using CoVeriTeam while using ontology to decipher relationships between the properties and tools, which machine learning algorithms will help by identifying possible patterns that would enhance the effectiveness (time of verification), completeness, and correctness of PLC verification devoid of false positives or negatives that could lead to hazards in the industrial control systems (ICSs) if not detected, corrected, and mitigated.

Committee

Dr. Hoda Mehrpouyan (Advisor), Dr. Nasir Eisty, Dr. Yantian Hou