AI-Assisted Model-Driven Security Engineering for Digital Twins: Toward an Automated Round-Trip[...]

Edtlab; Saclay; Sur place; EUR 17 000 - 21 000; Plein temps

Résumé du poste

Edtlab is seeking a candidate to pursue a thesis focused on the integration of AI in modeling complex cyber-physical systems. The role involves developing a framework to assist in Model-Driven Engineering and automating security engineering processes for digital twins.

Candidates should hold a Master's degree in computer science and be proficient in either English or French. Experience with digital twins and security modeling is advantageous.

Qualifications

• Master's degree in computer science required.
• Familiarity with digital twins is a plus.
• Proficiency in English or French.

Responsabilités

• Develop an AI-assisted Model-Driven Engineering framework.
• Automate round-trip security engineering processes.
• Create methods for updating architectural models based on security reports.
• Coordinate with the EDT program team and document findings.

Connaissances

Experience with Digital Twins

AI integration in modeling

Security modeling

Formation

Master degree in computer science

Outils

Digital Twins

AAS specification

Description du poste

The modeling of complex cyber-physical systems using standards such as UML and SysML remains a difficult task, currently lacking integration with Artificial Intelligence (AI) to assist the design process. While developers already use generative AI and prompting, these efforts are still not systematic. Integration of security concerns, either from standards or from experts knowledge, is mostly a manual process [2]. Round-trip engineering, which intend to synchronise design-time models and runtime execution feedback, remains under-explored [1]. Existing security platforms for Digital Twins (DT), are often proprietary and costly, and the process of applying security mitigations, or simulating scenarios before applying into the real infrastructure, remains unexplored.

Research Objectives

The primary goal of this thesis is to study and define an assisted Model-Driven Engineering (MDE) framework, that helps closing the loop between design and execution

• Systematizing AI Integration and security modeling: creating an AI-assisted environment within modeling tools to move beyond prompting, assisting designers with security concerns.
• Automating Round-Trip Security Engineering: creating a platform where the cycle of Design -> Execution -> Re-design has improved automation
• Security Injection and Synchronization: developing mechanisms to update architectural models based on security reports, attack simulations, and vulnerability scans (e.g., Mitre ATT&CK or CVE data).
• Cyber-Security Simulation: Enabling the execution/simulation of complex attack scenarios on a Digital Twin reference architecture to evaluate system configurations without risking physical infrastructure.

Proposed Methodology

The research will conduct a detailed research on current state of the art to refine and support the objectives previously presented. The study will enable to direct the research actions for a proposed framework. The basis artifacts initially used will be the Asset Administration Sheel (AAS) specification, which will serve as basis for DigitalTwin modeling. A formalisation of the framework and solution will be required, as well as the implementation and integration of a POC within the scope of the case studies of the EDT program.

Requirements

• Master degree in computer science
• English or French
• Experience with digital twins is a plus

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