Side-channel attacks represent a realistic and serious threat to the security of embedded
devices for already almost three decades. A variety of attacks and targets they can be …

Despite the rapid increase of data available to train machine-learning algorithms in many
domains, several applications suffer from a paucity of representative and diverse data. The …

The side-channel community recently investigated a new approach, based on deep
learning, to significantly improve profiled attacks against embedded systems. Previous …

Recently, several studies have been published on the application of deep learning to
enhance Side-Channel Attacks (SCA). These seminal works have practically validated the …

One of the main promoted advantages of deep learning in profiling side-channel analysis is
the possibility of skipping the feature engineering process. Despite that, most recent …

The adoption of deep neural networks for profiled side-channel attacks provides powerful
options for leakage detection and key retrieval of secure products. When training a neural …

Profiled side-channel attacks represent a practical threat to digital devices, thereby having
the potential to disrupt the foundation of e-commerce, the Internet of Things (IoT), and smart …

作为一类重要的信息安全产品, 密码产品中所使用的密码技术保障了信息的保密性,
完整性和不可抵赖性. 而侧信道攻击是针对密码产品的一类重要的安全威胁 …

Existing power analysis techniques rely on strong adversary models with prior knowledge of
the leakage or training data. We introduce side-channel analysis with unsupervised learning …

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 …