Abstract Deep-learning side-channel attacks, applying deep neural networks to are known that can easily attack some existing countermeasures such as masking and random jitter. While there have been many studies on profiled deep-learning a new approach involves learning non-profiled attacks was proposed in 2018. In our study, we investigate the structure of multi-layer perceptrons points interes...

Template Attack is widely accepted to be one of the most powerful side-channel attacks, because it is usually assumed that one has a full knowledge of targeted crypto devices and thus be well capable of characterizing the side-channel leakages. However, the question of whether Template Attack is really optimal in terms of leakage exploitation rate is still unclear. In this paper, we present a n...

Computer system performance is highly dependent on high access rate and low miss rate in the instruction cache, which also have implications on energy consumed by fetching instructions. Simulation experiments on a small scalar processor typical for embedded systems show that up to 20% of the overall processor energy is consumed in the instruction fetch path and that as much as 23% of the execut...

A novel optical fiber [comblike dispersion-profiled fiber (CDPF)] that consists of a chain of alternating segments of standard telecommunication fiber and dispersion-shifted fiber is proposed for the generation of a soliton pulse train based on nonlinear transformation of an optical beat signal. A totally integrated all-optical fiber source of a 59.1-GHz train of 2.2-ps solitons is demonstrated...

Content-based image retrieval (CBIR) has been heralded as a mechanism to cope with the increasingly larger volumes of information present in medical imaging repositories. However, generic, extensible CBIR frameworks that work natively with Picture Archive and Communication Systems (PACS) are scarce. In this article we propose a methodology for parametric CBIR based on similarity profiles. The a...