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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...
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 ...
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...
Convolutional neural networks (CNNs) is a category of deep neural networks that are primarily used for classifying image data. Yet, their continuous gain in popularity poses important privacy concerns...
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...
Robustness to modeling attacks is an important requirement for PUF circuits. Several reported Arbiter PUF com- positions have resisted modeling attacks. and often require huge computational resources ...
In recent years, deep learning has become an attractive ingredient to side-channel analysis (SCA) due to its potential to improve the success probability or enhance the performance of certain frequent...
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...
Homomorphic encryption (HE)---the ability to perform computation on encrypted data---is an attractive remedy to increasing concerns about data privacy in deep learning (DL). However, building DL model...
This paper presents the results of several successful profiled side-channel attacks against a secure implementation of the RSA algorithm. The implementation was running on a ARM Core SC 100 completed ...
This paper presents a very practical key recovery attack on Speck32/64 reduced to 11 rounds based on a novel type of differential distinguisher using machine learning. These distinguishers exceed dist...
This study compares the experimental results of Template Attacks (TA) and Deep Learning (DL) techniques called Multi Layer Perceptron (MLP) and Convolutional Neural Network (CNN), concurrently in fron...
Recent publications, such as [10] and [13], exploit the advantages of deep-learning techniques in performing Side-Channel Attacks. One example of the Side-Channel community interest for such technique...
This work describes a common framework for scale-invariant families of fully homomorphic schemes based on Ring-LWE, unifying the plaintext space and the noise representation. This new formalization al...
Deep learning technology has been evaluated to achieve the high-accuracy of state-of-the-art algorithms in a variety of AI tasks. Its popularity draws security researchers’ attention to the topic of p...

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