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The adoption of deep neural networks for profiled side-channel attacks provides different capabilities for leakage detection of secure products. Research papers provide a variety of arguments with res...
Machine learning is nowadays supplanting or extending human expertise in many domains ranging from board games to text translation. Correspondingly, the use of such tools is also on the rise in comput...
Leakage assessment of cryptographic implementations with side-channel analysis relies on two important assumptions: leakage model and the number of side-channel traces. In the context of profiled side...
Profiled side-channel attacks represent a practical threat to digital devices, thereby having the potential to disrupt the foundation of e-commerce, Internet-of-Things (IoT), and smart cities. In the ...
Machine learning techniques represent a powerful option in profiling side-channel analysis. Still, there are many settings where their performance is far from expected. In such occasions, it is very i...
Inspired by the literature on side-channel attacks against cryptographic implementations, we describe a framework for the analysis of location privacy. It allows us to revisit (continuous) re-identifi...
In Side Channel Analysis, masking is known to be a reliable and robust counter-measure. Recently, several papers have focused on the application of the Deep Learning (DL) theory to improve the efficie...
Physical Unclonable Functions (PUFs) have the potential to provide a higher level of security for key storage than traditional Non-Volatile Memory (NVM). However, the susceptibility of the PUF primiti...
Profiling side-channel attacks represent the most powerful category of side-channel attacks. There, we assume that the attacker has access to a clone device in order to profile the device. Additionall...
Profiled side-channel attacks are the most powerful attacks and they consist of two steps. The adversary first builds a leakage model, using a device similar to the target one, then it exploits this l...
Profiled side-channel attacks based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that ...
The static power consumption of modern CMOS devices has become a substantial concern in the context of the side-channel security of cryptographic hardware. Its continuous growth in nanometer-scaled te...
SM2 is a public key cryptography suite originating from Chinese standards, including digital signatures and public key encryption. Ahead of schedule, code for this functionality was recently mainlined...
In this paper we describe symbolic side-channel analysis techniques for detecting and quantifying information leakage, given in terms of Shannon and Min Entropy. Measuring the precise leakage is chall...
To provide insurance on the resistance of a system against side-channel analysis, several national or private schemes are today promoting an evaluation strategy, common in classical cryptography, whic...

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