Exploring and Optimizing Moving Target Defense Strategies Using Reinforcement Learning H/F
Stage Palaiseau (Essonne) IT development
Job description
Vacancy details
General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
2024-33920Description de l'unité
The French Atomic Energy and Alternative Energies Commission (CEA) is a major player in research, development and innovation. This technological research organization is active in three main areas: energy, information and health technologies, and defense. Recognized as an expert in its fields, CEA is fully integrated into the European research area and is expanding its presence internationally. The Laboratory for Systems and Technology Integration (LIST), located in the southern Île-de-France region (Saclay), has the mission of contributing to technology transfer and promoting innovation in the field of parallel computing systems.
Position description
Category
Engineering science
Contract
Internship
Job title
Exploring and Optimizing Moving Target Defense Strategies Using Reinforcement Learning H/F
Subject
The Digital Systems and Integrated Circuits Department (DSCIN) is a multidisciplinary research team focused, among others, on developing proactive security strategies, with a particular emphasis on the Moving Target Defense (MTD) approach. MTD aims to make systems more resilient to attacks by frequently altering their configurations, thus making it harder for attackers to gather reliable information.
To strengthen our MTD capabilities, we have already implemented various strategies, such as altering node mappings, to disrupt potential attacks. This internship aims to expand on these existing approaches by exploring new movement strategies, such as changing IP addresses or network paths, and developing new metrics to assess the effectiveness of these techniques.
Contract duration (months)
6 mois
Job description
The first task will be to identify additional system parameters that can be modified to further complicate attackers' efforts. The intern will also explore the optimal timings and methods for applying these changes while ensuring minimal impact on system performance. Additionally, the intern will explore the solution space using reinforcement learning to identify and optimize new MTD strategies.
During the internship, the student will:
Gain knowledge of our existing MTD strategies and their implementations,
Study the latest techniques in proactive system defense,
Propose innovative movement strategies and develop appropriate evaluation metrics,
Explore the solution space using reinforcement learning.
Applicant Profile
This internship is aimed at candidates in the final stages of their second cycle university education or engineering school.
Required level:
Master's Degree (Bac+5)
Duration:
6 months
Skills:
Required: Python,
Optional: Reinforcement Learning (RL), Network Security
Documents to provide:
CV + Cover Letter + Rank
Contact :
Kods TRABELSI, kods.trabelsi@
cea.fr
In line with CEA's commitment to integrating people with disabilities, this job is open to all.
Position location
Site
Saclay
Location
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