Emploi / Stage

Exploring and Optimizing Moving Target Defense Strategies Using Reinforcement Learning H/F

Challenge: Cyber security : hardware and sofware, Artificial Intelligence & data intelligence, New computing paradigms, including quantum, Communication networks, IOT, radiofrequencies and antennas, Cyber physical systems - sensors and actuators, Health and environment technologies, medical devices,
Type of Contract: Internship
Contract duration (nb of months) :
Institute : CEA-List
Location: Paris – Saclay
Level of study: Level 7
Desired start date : 1900-01-01

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.