Searched for: author%3A%22Wu%2C+L.%22
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Wu, L. (author)
For almost three decades, side-channel analysis has represented a realistic and severe threat to embedded devices' security. As a well-known and influential class of implementation attacks, side-channel analysis has been applied against cryptographic implementations, processors, communication systems, and, more recently, machine learning models....
doctoral thesis 2023
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Perin, G. (author), Wu, L. (author), Picek, S. (author)
The adoption of deep neural networks for profiling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature selection or trace preprocessing. This success comes with a high price: an extensive...
journal article 2023
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Picek, S. (author), Perin, G. (author), Mariot, L. (author), Wu, L. (author), Batina, Lejla (author)
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 applied to have been introduced, and while the area of side-channel attacks and their mitigation is very well-researched, it is yet to be consolidated. Deep learning...
journal article 2023
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Kerkhof, Maikel (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)
Deep learning is a powerful direction for profiling side-channel analysis as it can break targets protected with countermeasures even with a relatively small number of attack traces. Still, it is necessary to conduct hyperparameter tuning to reach strong attack performance, which can be far from trivial. Besides many options stemming from the...
journal article 2023
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Wu, L. (author), Weissbart, L.J.A. (author), Krcek, M. (author), Li, H. (author), Perin, G. (author), Batina, Lejla (author), Picek, S. (author)
The efficiency of the profiling side-channel analysis can be significantly improved with machine learning techniques. Although powerful, a fundamental machine learning limitation of being data-hungry received little attention in the side-channel community. In practice, the maximum number of leakage traces that evaluators/attackers can obtain is...
journal article 2023
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Remmerswaal, Mick G.D. (author), Wu, L. (author), Tiran, Sébastien (author), Mentens, Nele (author)
Template attacks (TAs) are one of the most powerful side-channel analysis (SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called points of interest (POIs), to extract the...
journal article 2023
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Fieback, M. (author), Cardoso Medeiros, G. (author), Wu, L. (author), Aziza, Hassen (author), Bishnoi, R.K. (author), Taouil, M. (author), Hamdioui, S. (author)
Resistive RAM (RRAM) is a promising technology to replace traditional technologies such as Flash, because of its low energy consumption, CMOS compatibility, and high density. Many companies are prototyping this technology to validate its potential. Bringing this technology to the market requires high-quality tests to ensure customer...
journal article 2022
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Wu, L. (author), Rao, Siddharth (author), Taouil, M. (author), Marinissen, Erik Jan (author), Kar, Gouri Sankar (author), Hamdioui, S. (author)
The manufacturing process of STT-MRAM requires unique steps to fabricate and integrate magnetic tunnel junction (MTJ) devices which are data-storing elements. Thus, understanding the defects in MTJs and their faulty behaviors are paramount for developing high-quality test solutions. This article applies the advanced device-aware test to...
journal article 2022
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Wu, L. (author), Perin, G. (author), Picek, S. (author)
In the last decade, machine learning-based side-channel attacks have become a standard option when investigating profiling side-channel attacks. At the same time, the previous state-of-the-art technique, template attack, started losing its importance and was more considered a baseline to compare against. As such, most of the results reported...
journal article 2022
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Perin, G. (author), Wu, L. (author), Picek, S. (author)
Deep learning-based side-channel analysis (SCA) represents a strong approach for profiling attacks. Still, this does not mean it is trivial to find neural networks that perform well for any setting. Based on the developed neural network architectures, we can distinguish between small neural networks that are easier to tune and less prone to...
book chapter 2022
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Perin, G. (author), Wu, L. (author), Picek, S. (author)
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 publications consider feature selection as the attacked interval from the side-channel measurements is pre-selected. This is similar to the worst-case security...
journal article 2022
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Gebregiorgis, A.B. (author), Wu, L. (author), Münch, Christopher (author), Rao, Siddharth (author), Tahoori, Mehdi B. (author), Hamdioui, S. (author)
STT-MRAM has long been a promising non-volatile memory solution for the embedded application space owing to its attractive characteristics such as non-volatility, low leakage, high endurance, and scalability. However, the operating requirements for high-performance computing (HPC) and low power (LP) applications involve different challenges....
conference paper 2022
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Rijsdijk, Jorai (author), Wu, L. (author), Perin, G. (author)
Deep learning-based side-channel attacks are capable of breaking targets protected with countermeasures. The constant progress in the last few years makes the attacks more powerful, requiring fewer traces to break a target. Unfortunately, to protect against such attacks, we still rely solely on methods developed to protect against generic...
conference paper 2022
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Kerkhof, Maikel (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)
The deep learning-based side-channel analysis represents one of the most powerful side-channel attack approaches. Thanks to its capability in dealing with raw features and countermeasures, it becomes the de facto standard approach for the SCA community. The recent works significantly improved the deep learning-based attacks from various...
conference paper 2022
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Wu, L. (author), Perin, G. (author), Picek, S. (author)
Deep learning-based side-channel analysis is rapidly positioning itself as a de-facto standard for the most powerful profiling side-channel analysis.The results from the last few years show that deep learning techniques can efficiently break targets that are even protected with countermeasures. While there are constant improvements in making...
conference paper 2022
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Wu, L. (author)
As STT-MRAM mass production and deployment in industry is around the corner, high-quality yet cost-efficient manufacturing test solutions are crucial to ensure the required quality of products being shipped to end customers. This dissertation focuses on STT-MRAM testing, covering three abstraction levels: manufacturing defects, fault models, and...
doctoral thesis 2021
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Rijsdijk, J. (author), Wu, L. (author), Perin, G. (author), Picek, S. (author)
Deep learning represents a powerful set of techniques for profiling side-channel analysis. The results in the last few years show that neural network architectures like multilayer perceptron and convolutional neural networks give strong attack performance where it is possible to break targets protected with various coun-termeasures....
journal article 2021
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Wu, L. (author), Rao, Siddharth (author), Taouil, M. (author), Marinissen, Erik Jan (author), Kar, Gouri Sankar (author), Hamdioui, S. (author)
Understanding the defects in magnetic tunnel junctions (MTJs) and their faulty behaviors are paramount for developing high-quality tests for STT-MRAM. This paper characterizes and models intermediate (IM) state defects in MTJs; IM state manifests itself as an abnormal third resistive state, apart from the two bi-stable states of MTJ. We...
conference paper 2021
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Wu, L. (author), Rao, Siddharth (author), Taouil, M. (author), Marinissen, Erik Jan (author), Kar, Gouri Sankar (author), Hamdioui, S. (author)
Understanding the manufacturing defects in magnetic tunnel junctions (MTJs), which are the data-storing elements in STT-MRAMs, and their resultant faulty behaviors are crucial for developing high-quality test solutions. This paper introduces a new type of MTJ defect: synthetic anti-ferromagnet flip (SAFF) defect, wherein the magnetization in...
conference paper 2021
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Wu, L. (author), Perin, G. (author)
In recent years, the advent of deep neural networks opened new perspectives for security evaluations with side-channel analysis. Profiling attacks now benefit from capabilities offered by convolutional neural networks, such as dimensionality reduction and the inherent ability to reduce the trace desynchronization effects. These neural...
conference paper 2021
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