Searched for: subject%3A%22Attack%22
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Pigmans, Max (author)
Most of the adversarial attacks suitable for attacking decision tree ensembles work by doing multiple local searches from randomly selected starting points, around the to be attacked victim. In this thesis we investigate the impact of these starting points on the performance of the attack, and find that the starting points significantly impact...
master thesis 2024
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Aljuffri, A.A.M. (author)
The security of electronic devices holds the greatest importance in the modern digital era, with one of the emerging challenges being the widespread occurrence of hardware attacks. The aforementioned attacks present a substantial risk to hardware devices, and it is of utmost importance to comprehend the potential detrimental effects they may...
doctoral thesis 2024
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Duroyon, Marin (author)
Acoustic side-channel attacks (SCAs) use audio produced by a system to bypass traditional security measures to extract sensitive information. Human interface devices, such as keyboards, have been the focus of such attacks, however, computer mice are input devices that are currently in a research gap. This paper explores the security risks the...
master thesis 2024
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Nenovski, Lazar (author)
Abstract— Federated Learning (FL) makes it possible for a network of clients to jointly train a machine learning model, while also keeping the training data private. There are several approaches when designing a FL network and while most existing research is focused on a single-server design, new and promising variations are arising that make...
bachelor thesis 2024
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van der Meulen, Jan (author)
Federated learning (FL) is a privacy preserving machine learning approach which allows a machine learning model to be trained in a distributed fashion without ever sharing user data. Due to the large amount of valuable text and voice data stored on end-user devices, this approach works particularly well for natural language processing (NLP)...
bachelor thesis 2024
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Mladenović, Todor (author)
Multi-Server Federated Learning (MSFL) is a decentralised way to train a global model, taking a significant step toward enhanced privacy preservation while minimizing communication costs through the use of edge servers with overlapping reaches. In this context, the FedMes algorithm facilitates the aggregation of gradients, contributing to the...
bachelor thesis 2024
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Simonov, Alex (author)
Machine learning, a pivotal aspect of artificial intelligence, has dramatically altered our interaction with technology and our handling of extensive data. Through its ability to learn and make decisions from patterns and previous experiences, machine learning is growing in influence on different aspects of our lives. It is, however, shown that...
master thesis 2024
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Xiao, J. (author), Wang, L. (author), Qin, Z. (author), Bauer, P. (author)
Communication-based distributed secondary control is deemed necessary to restore the state of islanding AC microgrids to set points. As its limited global information, the microgrids become vulnerable to cyber-attacks, which by falsifying the communicating singles, like the angular frequency, can disturb the power dispatch in the microgrids...
journal article 2024
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Zhao, Z. (author), Huang, J. (author), Chen, Lydia Y. (author), Roos, S. (author)
Generative Adversarial Networks (GANs) are increasingly adopted by the industry to synthesize realistic images using competing generator and discriminator neural networks. Due to data not being centrally available, Multi-Discriminator (MD)-GANs training frameworks employ multiple discriminators that have direct access to the real data....
conference paper 2024
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Anghel, R.I. (author), Vetrivel, Swaathi (author), Turcios Rodriguez, E.R. (author), Sameshima, Kaichi (author), Makita, Daisuke (author), Yoshioka, Katsunari (author), Hernandez Ganan, C. (author), Zhauniarovich, Y. (author)
Remotely Triggered Black Hole (RTBH) is a common DDoS mitigation approach that has been in use for the last two decades. Usually, it is implemented close to the attack victim in networks sharing some type of physical connectivity. The Unwanted Traffic Removal Service (UTRS) project offers a free, global, and relatively low-effort-to-join and...
conference paper 2024
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Gao, Yuxing (author)
The rapid advancement in autonomous driving technology underscores the importance of studying the fragility of perception systems in autonomous vehicles, particularly due to their profound impact on public transportation safety. These systems are of paramount importance due to their direct impact on the lives of passengers and pedestrians....
master thesis 2023
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Ho, Björn (author)
A searchable symmetric encryption (SSE) scheme allows a user to securely perform a keyword search on an encrypted database. This search capability is useful but comes with the price of unintentional information leakage. An attacker abuses leakage to steal confidential information by launching SSE attacks. In this work, our goal is to design a...
master thesis 2023
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Zou, Jinyi (author)
This thesis aims to assess robustness of networks by evaluating the performance of node attack strategies, the applicability and accuracy of different approaches, and to increase robustness of networks through analysing protecting methods, including link addition and node protection strategies. To be specific, the relative size of the Largest...
master thesis 2023
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Băbălău, Ion (author)
In an era where cyber threats evolve with alarming speed and sophistication, the role of Security Operation Centers (SOCs) has become increasingly pivotal in safeguarding digital infrastructures. SOCs serve as the frontline defence against malicious entities, where they continuously monitor and analyze network traffic, as well as the activity of...
master thesis 2023
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Muntenaar, Laura (author)
Demand for smart, Internet-connected devices and other electronics has increased dramatically in recent years. This increase in demand for technological devices, driven by advancements in Artificial Intelligence (AI), the Internet of Things (IoT), and autonomous systems, has exposed the digital system to potential security threats. As more...
master thesis 2023
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Vian, Giacomo (author)
The proliferation of Distributed Energy Resources (DERs) is decentralizing the power system, with more and more capacity installed in the distribution grids. Concurrently, the energy sector is embracing the Internet of Things (IoT) paradigm, resulting in the emergence of the Internet of Energy. However, this transformation introduces new...
master thesis 2023
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de Bie, Rokus (author)
For the past 2000 years river training works have been performed on the Dutch rivers. These training works have shaped the river system of today. Another result of the river training works, especially over the last two centuries, is a decrease in biodiversity. To protect the biodiversity some floodplains in the Netherlands have been classified...
master thesis 2023
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Najm, Z. (author)
doctoral thesis 2023
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Huang, Ruoyu (author)
Internet of Things (IoT) devices regularly process sensitive data, including personal information. Therefore, ensuring their security is crucial to avoid damage and prevent data breaches. The Advanced Encryption Standard (AES) is generally regarded as one of the most popular cryptographic algorithms for ensuring data security. Typical...
master thesis 2023
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Köylü, T.C. (author)
Machine learning has gained a lot of recognition recently and is now being used in many important applications. However, this recognition was limited in the hardware security area. Especially, very few approaches depend on this powerful tool to detect attacks during operation. This thesis reduces this gap in the field of fault injection attack...
doctoral thesis 2023
Searched for: subject%3A%22Attack%22
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