A5023438943- Cryptographic Implementations and Security
- Advanced Malware Detection Techniques
- Physical Unclonable Functions (PUFs) and Hardware Security
- Chaos-based Image/Signal Encryption
- Network Security and Intrusion Detection
- Digital Media Forensic Detection
- Security and Verification in Computing
- Coding theory and cryptography
- Internet Traffic Analysis and Secure E-voting
- Wireless Signal Modulation Classification
- Smart Grid Security and Resilience
- Integrated Circuits and Semiconductor Failure Analysis
- Digital and Cyber Forensics
- Adversarial Robustness in Machine Learning
- Information and Cyber Security
- Electrostatic Discharge in Electronics
- Cardiac electrophysiology and arrhythmias
- Particle Detector Development and Performance
- Parallel Computing and Optimization Techniques
- Distributed and Parallel Computing Systems
- Spam and Phishing Detection
- Neural Networks and Applications
- Bacillus and Francisella bacterial research
- Anomaly Detection Techniques and Applications
- Security, Politics, and Digital Transformation
Institut de Recherche en Informatique et Systèmes Aléatoires
2014-2024
Centre National de la Recherche Scientifique
2015-2024
Université de Rennes
2018-2024
Institut national de recherche en informatique et en automatique
2018-2022
State Key Laboratory of Cryptology
2014-2022
Institut für Regionale Innovation und Sozialforschung
2021
Inria Rennes - Bretagne Atlantique Research Centre
2018
Laboratoire Traitement et Communication de l’Information
2014-2017
Télécom Paris
2012-2017
Institut Mines-Télécom
2014-2016
Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing new Network instance reach high performance number of considered datasets. We compare our neural network the one designed particular dataset masking...
We concentrate on machine learning techniques used for profiled sidechannel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, instance Hamming weight or distance leakage models. In order to deal with data, we use various balancing show that most them help mounting successful attacks when data is highly imbalanced. Especially, results SMOTE technique encouraging, since observe some where it reduces number necessary measurements more than 8 times....
The field of side-channel analysis has made significant progress over time. Side-channel is now used in practice design companies as well test laboratories, and the security products against attacks significantly improved. However, there are still some remaining issues to be solved for become more effective. consists two steps, commonly referred identification exploitation. understanding leakage building suitable models. exploitation using identified models extract secret key. In scenarios...
Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptographic implementations protected with countermeasures. In this paper, we start by proposing new Network instance reach high performance number of considered datasets. We compare our neural network the one designed particular dataset masking...
Profiled side-channel attacks represent a practical threat to digital devices, thereby having the potential disrupt foundation of e-commerce, Internet Things (IoT), and smart cities.In profiled attack, adversary gains knowledge about target device by getting access cloned device.Though these two devices are different in realworld scenarios, yet, unfortunately, large part research works simplifies setting using only single for both profiling attacking.There, portability issue is conveniently...
Side-channel attacks represent a powerful category of against cryptographic devices. Still, side-channel analysis for lightweight ciphers is much less investigated than instance AES. Although intuition may lead to the conclusion that are weaker in terms resistance, remains be confirmed and quantified. In this paper, we consider various metrics which should provide an insight on resistance attacks. particular, non-profiled scenario use theoretical confusion coefficient empirical optimal...
Profiled side-channel attacks consist of several steps one needs to take. An important, but sometimes ignored, step is a selection the points interest (features) within measurement traces. A large majority related works start analyses with an assumption that features are preselected. Contrary this assumption, here, we concentrate on feature step. We investigate how advanced techniques stemming from machine learning domain can be used improve attack efficiency. To end, provide systematic...
In this paper we present improvements of the algebraic side-channel analysis Advanced Encryption Standard (AES) proposed in [1]. particular, optimize representation AES and obtained information order to speed up attack increase success rate. We study performance our both known unknown plaintext/ciphertext scenarios. Our experiments indicate that cases amount required is less than one attacks introduced Furthermore, introduce a method for error handling, which allows improved escape...
Modern electronic systems become evermore complex, yet remain modular, with integrated circuits (ICs) acting as versatile hardware components at their heart. Electronic design automation (EDA) for ICs has focused traditionally on power, performance, and area. However, given the rise of hardware-centric security threats, we believe that EDA must also adopt related notions like secure by composition hardware. Despite various promising studies, argue some aspects still require more efforts,...
In the light of implementation attacks a better understanding complex circuits security sensitive applications is an important issue. Appropriate evaluation tools and metrics are required to understand origin flaws within design process. The selected leakage model has significant influence on reliability results concerning side-channel resistance cryptographic implementation. this contribution we introduce methods, which determine accuracy characterization allow quantify signal-to-noise...