Recent advancements in artificial intelligence (AI) technology have raised concerns about
the ethical, moral, and legal safeguards. There is a pressing need to improve metrics for …

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 …

Leakage detection usually refers to the task of identifying data-dependent information in side-
channel measurements, independent of whether this information can be exploited. Detecting …

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 …

Masked implementations of cryptographic algorithms are often used in commercial
embedded cryptographic devices to increase their resistance to side channel attacks. In this …

Variability is a central issue in deep submicron technologies, in which it becomes
increasingly difficult to produce two chips with the same behavior. While the impact of …

Abstract The Internet of Things (IoT) ecosystem needs Intrusion Detection Systems (IDS) to
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …

In this study, the authors examine the relationship between and the efficiency of different
approaches to standard (univariate) differential power analysis (DPA) attacks. The authors …

With increasing expansion of the Internet of Things, embedded devices equipped with
cryptographic modules become an important factor to protect sensitive data. Even though …

We introduce in this paper a technique in which we apply correlation analysis using only
one execution power curve during an exponentiation to recover the whole secret exponent …