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CNRS

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PhD in Improving Reverse Engineering via Side-Channel Analysis CNRS in France

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 14, 2026

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Country

France

University

CNRS

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Keywords

Computer Science
Electrical Engineering
Information Technology
Time Series Analysis
Probabilistic Modeling
Anomaly Detection
Reverse Engineering
Semantic Segmentation
Embedded System
ML

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About this position

This PhD project is about improving reverse engineering for side-channel analysis on embedded systems. The thesis targets situations where security assessment of a device must begin with a preparatory detection phase, for example to identify cryptographic primitives in traces for future observation attacks or to locate target routines for fault-based attacks.

The goal is to design non-profiled methods and tools that can automate this detection stage while also leveraging an attacker’s prior knowledge. The work sits at the intersection of side-channel reverse engineering and well-known time-series problems such as motif discovery, anomaly detection, and semantic segmentation.

Research will address the specific challenges of side-channel traces on complex SoC platforms, including noise and jitter, and will explore approaches combining machine learning, probabilistic models, and exact time-series metrics. The thesis also highlights broader scenarios such as reverse engineering of bootloaders and discovery of neural network architectures.

The project is hosted by the TIMA laboratory, a public research lab under the supervision of CNRS, Grenoble INP, and Université Grenoble Alpes. TIMA is described as a cosmopolitan team of around 150 people, working on specification, design, verification, testing, CAD tools, and design-support methods for embedded systems, within a collaborative environment connected to industrial and academic partners.

Funding details

Available

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