PhD-Improving the efficiency of AI models for malware analysis F/H

Job title:

PhD-Improving the efficiency of AI models for malware analysis F/H

Company:

Orange

Job description

about the roleYour role is to carry out thesis work on: Improving the efficiency, interpretation and robustness of AI models for malware analysis”· Global context and problematic of the subjectUse our expertise in cybersecurity to combat future malware more effectively, as it becomes increasingly powerful and complex.AI models for the detection of cyber threats are coming up against the ever more rapid development and refinement of attackers, now aided by generative AI, and so-called Malware-As-A-Service markets.Through new AI models, improving robustness and explainability will help to fill these gaps, relying not just on data, but also on business knowledge.· Scientific objective – results and challengesThe aim of the thesis is to propose a generic framework for integrating business knowledge and expertise, in order to improve AI models for cyber threat analysis, with a use case in malware detection.Main challenges:1) Mastering and integrating new AI technologies (LLM, neuro-symbolic AI, etc.) to address cyber issues.2) Improving collaboration between cyber players (analysts, reversers) and AI/ML researchers.3) Integrate business knowledge on malware (YARA, Mitre Att&ck, empirical knowledge…).4) Address issues related to the robustness and explicability of models and improve confidence.Main expected results:1) State of the art on neuro-symbolic AI and LLMs, and their combined integration with analysis models for cybersecurity.2) Proposal of a generic framework applicable to malware detection, and to other cybersecurity topics.3) Implementation of a prototype for advanced malware detection and analysisabout you· Skills (scientific and technical) and personal qualities required by the positionAdvanced knowledge of Machine Learning / Deep Learning, particularly recent technologies (LLM, Transformers)Cybersecurity skills, particularly in malware analysis and reverse engineering· Education required (Master’s degree, engineering diploma, PhD, scientific and technical field, etc.)Master’s or engineering degree (Cyber and/or AI)· Desired experience (internships, …)Internship in the fields of AI/CyberA first experience in research (internship, project) will be appreciatedadditional informationThe idea of a new paradigm in AI thanks to new technologies such as LLMs or neuro-symbolic AI is beginning to emerge within the scientific community. Specialized companies such as DeepMind are already integrating this technology into their work to improve the efficiency of their models. In the field of cybersecurity, these technologies are slow to find their place, with applications that are often “data” rather than “business” oriented. By putting business needs back at the center of our thinking, we’ll be able to position ourselves at the forefront of this field.departmentOrange 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 Innovation, you will be part of a research team specialized in cybersecurity. The cyberservices team develops new research themes and innovations in cybersecurity for Orange’s operational teams, such as CERT and Orange Cyberdefense. In particular, the team is a leader in the use of artificial intelligence to detect cyberthreats and improve cybersecurity tools.contractThesis

Expected salary

Location

Cesson-Sévigné, Ille-et-Vilaine

Job date

Tue, 18 Mar 2025 23:25:04 GMT

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