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We take advantage of a recently published open source implementation of the AES protected with a mix of countermeasures against side-channel attacks to discuss both the challenges in protecting COTS d...
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...
In this article, we demonstrate practical side-channel assisted chosen-ciphertext attacks (CCA) over multiple CCA-secure lattice-based public-key encryption schemes (PKE) and key-encapsulation mechani...
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...
CSIDH is a recent quantum-resistant primitive based on the difficulty of finding isogeny paths between supersingular curves. Recently, two constant-time versions of CSIDH have been proposed: first by ...
Collision side-channel attacks are efficient attacks against cryptographic implementations, however, optimal collision side-channel attacks and how to compute them efficiently is an open question. In ...
Collision side-channel attacks are efficient attacks against cryptographic implementations, however, optimal collision side-channel attacks and how to compute them efficiently is an open question. In ...
This article, for the first time, demonstrates Cross-device Deep Learning Side-Channel Attack (X-DeepSCA), achieving an accuracy of >99.9%>99.9%, even in presence of significantly higher inter-device ...
We describe SKIVA, a customized 32-bit processor enabling the design of software countermeasures for a broad range of implementation attacks covering fault injection and side-channel analysis of timin...
The past few decades have seen significant progress in practically realizable quantum technologies. It is well known since the work of Peter Shor that large scale quantum computers will threaten the s...
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...
Recent combined collision attacks have shown promising results for exploiting side-channel leakage information from both divide-and-conquer and analytical distinguishers. However, divide-and-conquer d...
Deep learning side-channel attacks are an emerging threat to the security of implementations of cryptographic algorithms. The attacker first trains a model on a large set of side-channel traces captur...
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 ...
A recent line of research has investigated a new profiling technique based on deep learning as an alternative to the well-known template attack. The advantage of this new profiling approach is twofold...

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