PhD-Cooperation schemes & heterogeneous algorithmic approaches F/M

Orange Innovation brings together the research and innovation activities and expertise of the Group's entities and countries. We work every day to ensure that Orange is recognized as an innovative operator by its customers and we create value for the Group and the Brand in each of our projects. With 720 researchers, thousands of marketers, developers, designers and data analysts, it is the expertise of our 6,000 employees that fuels this ambition every day.

Orange Innovation anticipates technological breakthroughs and supports the Group's countries and entities in making the best technological choices to meet the needs of our consumer and business customers. Within the Innovation department, you will be integrated into a research team at the forefront of innovation and expertise in artificial intelligence and cybersecurity. You will be part of a research ecosystem involved in the optimization of networks and services of the Orange Group. The thesis will take place at Orange Research and at the EURECOM laboratory (Sophia

Tech). It will be supervised academically by Dr. Raphaël Troncy and industrially by Dr. Lionel Tailhardat. Your role is to conduct thesis research on the topic of \"Optimizing cybersecurity incident diagnostics in the era of generative AI: cooperation schemes and self-orchestration of heterogeneous algorithmic approaches under time and explainability constraints.\"

Global Context and Problem Statement

Modern computer networks and telecommunications services, due to their complexity, pose unprecedented challenges for rapid incident diagnosis. The dispersion of expertise and technical approaches within an organization notably represents an opportunity for malicious actors. Therefore, it is crucial to develop methods and tools for rapid and effective diagnosis in these complex environments.

Scientific Objective - Challenges and Expected Results

To understand how to automatically orchestrate, under time and explainability constraints, various algorithmic...