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Unsupervised Deep Learning-based Side-channel Analysis

Savu, Ioana (author)

Side-channel attacks (SCA) play a crucial role in assessing the security of the implementation of cryp- tographic algorithms. Still, traditional profiled attacks require a nearly identical reference device to the target, limiting their practicality. This thesis focuses on non-profiled SCA, which provides a re- alistic alternative when the...

master thesis 2023

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Methodologies for deep learning SCA: An analysis on the design and construction of convolutional neural networks for side-channel datasets

Blankendal, Philip (author)

Side-channel attacks leverage the unintentional leakage of information that indirectly relates to cryptographic secrets such as encryption keys. Previous settings would involve an attacker conducting some manual-statistical analysis to exploit this data and retrieve sensitive information from the target. With the adoption of deep learning...

master thesis 2022

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Hardware-based implementations in Side-Channel Analysis: A comparison study of DL SCA attacks against HW and SW AES and a novel methodology

Bubberman, Wolf (author)

Side-Channel Attacks (SCA) attempt to recover the secret cryptographic key from an electronic device by exploiting the unintended physical leakages of said device. With the devices that are being attacked becoming more sophisticated, so is SCA. In the past few years, the focus of the research in the field of SCA shifted towards the application...

master thesis 2022

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On the use of ResNet architec- tures for Side-Channel Analysis

Karayalçin, Sengim (author)

Some of the most prominent types of attacks against modern cryptographic implementations are side-channel attacks. These attacks leverage some unintended, often physical, leakage of the implementation to retrieve secret information. In recent times, a large part of the focus of side-channel research has been on deep learning methods. These...

master thesis 2022

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Neuroevolution Applied to Profiled Side-Channel Attacks

Schijlen, Fiske (author)

Side-channel attacks (SCA) can obtain secret information related to the private key used during encryption executed on some device by exploiting leakage in power traces produced by the device. In recent years, researchers found that a neural network (NN) can be employed to execute a powerful profiled SCA, even on targets protected with...

master thesis 2022

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Semi-Supervised Learning In Side-Channel Attacks

Slooff, Tom (author)

One of the most potent attacks against cryptographic implementations nowadays is side-channel attacks. Side-channel attacks use unintended leakages in the implementation, for example, electromagnetic radiation, to retrieve the secret key. Over time side-channel attacks have become more powerful, and recently the community has shifted towards...

master thesis 2021

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Deep Learning Leakage Assessment

Berg, Chris (author)

In this work, we explore the topic of Machine Learning (ML) in the area of Leakage Assessment (LA), a subsection of the field of Side-Channel Analysis (SCA). We focus on Deep Learning Leakage Assessment (DL-LA), as proposed by Wegener et al., and its relation to the established Test Vector Leakage Assessment (TVLA). We will do this in the...

master thesis 2021

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Side-channel Attacks on Inner Rounds of AES and PRESENT: A deeper look into the inner rounds of SPN based block ciphers and how this vision can help us attack the intermediate bytes using Deep Learning

Swaminathan, Sudharshan (author)

Side-channel attacks (SCA) focus on vulnerabilities caused by insecure implementations and exploit them to deduce useful information about the data being processed or the data itself through leakages obtained from the device. There have been many studies exploiting these side-channel leakages, and most of the state-of-the-art attacks have been...

master thesis 2021

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On Code-based Cryptosystems using binary codes with large minimum distance: Post-Quantum Cryptography

Yorgova, Radinka (author)

Code-Based Cryptography is a branch of the Post-Quantum Cryptography research area. As such, its focus is on developing algorithms that can be used in the current communication systems to secure them against an adversary powered in the (near) future by a quantum computer. A code-based type cryptosystem is a public key cryptosystem that is...

master thesis 2021

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Loss functions for profiled side-channel analysis: An analysis of loss functions and the application of multi­-loss functions for deep learning in the SCA domain

Kerkhof, Maikel (author)

Deep learning techniques have become the tool of choice for side-channel analysis. In recent years, neural networks like multi-layer perceptrons and convolutional neural networks have proven to be the most powerful instruments for performing side-channel analysis. Recent work on this topic has focused on different aspects of these techniques,...

master thesis 2021

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Adversarial Examples as a defense against Side-Channel Attacks: A novel approach for countermeasure design

Korpas Kamarianos, Alexandros (author)

Over the last decades, side-channel attacks (SCAs) have been proven as a substantial weakness of cryptographic devices, while the recent growth of deep learning (DL) dramatically improved the performance of SCA. More and more researches present ways to build lightweight deep neural network (DNN) models that can retrieve the secret encryption key...

master thesis 2021

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Backdoor Attacks in Neural Networks

Koffas, Stefanos (author)

Deep learning has made tremendous success in the past decade. As a result, it is becoming widely deployed in various safety and security-critical applications like autonomous driving, malware detection, fingerprint identification, and financial fraud detection. It was recently shown that deep neural networks are susceptible to multiple attacks...

master thesis 2021

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Side-channel analysis with graph neural networks

de Bruijn, Vasco (author)

In cyber security, side-channel attacks (SCA) are of interest because they target the vulnerabilities in implementation rather than inherent vulnerabilities in the algorithm. Profiled SCA is especially interesting as it assumes that the adversary has unlimited access to a clone device that can generate sufficient traces to create a profile of...

master thesis 2021

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Data Augmentation Techniques using Generative Adversarial Neural Networks on Side Channel Analysis

Vlogiaris, Achilleas (author)

Side-channel Attacks can be performed in various ways by measuring the power consumption, the electromagnetic emission, or even by measuring an algorithm's execution time on the targeted device. More or less sophisticated methods can be used to utilize this information in order to perform a Side-channel attack, more specifically by training...

master thesis 2021

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Side-channel leakages: from different target devices

Arora, Vipul (author)

The advances in cryptography have enabled the features of confidentiality, security, and integrity in the digital space.<br/>The information about the working of the digital system is used to perform side-channel attacks.<br/>These attacks exploit the physics of the system rather than targeting the mathematical complexity of algorithms.<br/>Side...

master thesis 2020

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Reinforcement Learning for Profiled Side-Channel Analysis: Applications of Q-Learning in the SCA Domain

Rijsdijk, Jorai (author)

Side-channel attacks (SCA), which use unintended leakage to retrieve a secret cryptographic key, have become more sophisticated over time. With the recent successes of machine learning (ML) and especially deep learning (DL) techniques against cryptographic implementations even in the presence of dedicated countermeasures, various methods have...

master thesis 2020

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On the Sequential Data Models in Side-Channel Analysis: RNN, LSTM, GRU Hyperparameters, Autoencoder and Embedding Layer

Mulders, Maurits (author)

A side-channel attack is performed by analyzing unwanted physical leakage to achieve a more effective attack on the cryptographic key. An attacker performs a profiled attack when he has a physical and identical copy of the target device, meaning the attacker is in full control of the target device. Therefore, these profiled attacks are known as...

master thesis 2020

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Global Monitoring and Visualization of the Internet

Huisman, R.F. (author), Weegink, S. (author), Kaptein, S.B.M. (author), Jeleniewski, A.J. (author), Saveur, T. (author)

The internet consists of many networks connected by the BGP protocol and can easily be manipulated by a hacker. Every day, hackers reroute internet traffic and use that to impersonate entities such as companies, devices and humans. To detect this rerouting, which is also know as a route leak, a BGP monitor can be used. A BGP monitor checks...

bachelor thesis 2020

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Improving machine learning based side-channel analysis: can dropout be dropped out?

Kok, Jim (author)

Analysing physical leakages (e.g. power consumption and electromagnetic radiation) of cryptographic devices can be used by adversaries to extract secret keys. Over the last couple of years, researchers have shown that machine learning has potential for this process. Machine learning models need to be fine-tuned to enhance key extraction...

bachelor thesis 2020

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A Literature Study into Hyperparameter Systematization for Deep Learning-based Side-Channel Analysis

Mulder, Doreen (author)

With the recent increase in computational power, deep learning is being applied in many different fields. Deep learning has produced promising results in the field of side-channel analysis. However, the algorithms used to construct deep neural networks remain black boxes, which makes it hard to fully employ the capabilities of attacks performed...

bachelor thesis 2020