Searched for: subject%3A%22Privacy%22
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Stokkink, Q.A. (author)
The digital world is evolving toward representing - and serving the interconnection of - natural persons. Instead of depending on the intrastructure of Big Tech companies and governments, users can cooperate and use their hardware to form public infrastructure. Instead of existing by virtue of a reference in some institution's database, users...
doctoral thesis 2024
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van der Wel, Iris (author)
Data-driven health research, specifically the development of AI models, is hampered by poor data availability and associated administrative burdens, caused complex and fragmented data protection regulation. To reap the benefits of using high quality health data, while safeguarding data protection of patients, the synthetic data generation is...
master thesis 2024
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van Gend, Thijmen (author)
Privacy-enhancing technologies (PETs) have historically been used for safeguarding individual privacy from both public and private interference. But lately, tech companies have started using PETs as one instrument for the expansion of their power over different actors, as appears to be unfolding in the case of Amazon’s Sidewalk service: a United...
master thesis 2024
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Coggins, T.N. (author)
In the introduction of this thesis, I contend that robot ethics, as a research field, generally treats privacy as the appropriate distribution of information, and therefore overlooks privacy concerns raised by robots beyond this conceptualization’s purview. I illustrate this contention by evaluating a hypothetical case involving a household...
doctoral thesis 2024
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Kouwenhoven, Robin (author)
Foremost among the challenges of the Bitcoin blockchain is the scalability bottleneck. To address this issue, the Lightning Network, a payment channel network, was created. Lightning is a payment channel network that is source-routed and uses onion routing, like Tor. However, unlike Tor, the routing path is determined by optimizing a cost...
master thesis 2024
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Out, Annabelle (author)
This project explores the prospects for interior design in a dual purpose train that can run both day and night for improved utilization and comfort.<br/><br/>Contemporary trains are categorized as either exclusively for daytime or nighttime use. Their interiors limit them to specific temporal contexts. For instance, in daytime trains,...
master thesis 2024
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Bestebreur, Timon (author)
The versatility of the internet enables many applications that play an increasingly bigger role in our society. However, users have little control over the route that their internet traffic takes, which prevents them from controlling who sees their packets and how their traffic is handled. Researchers have proposed an extension to the internet,...
master thesis 2024
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Van Opstal, Quinten (author)
Federated learning provides a lot of opportunities, especially with the built-in privacy considerations. There is however one attack that might compromise the utility of federated learning: backdoor attacks [14]. There are already some existing defenses, like flame [13] but they are computationally expensive [14]. This paper evaluates a version...
bachelor thesis 2024
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Ghasia, Zahra (author)
The use of Electronic Health Records (EHRs) has seen a breakthrough in clinical research for personalized treatments (Hamburg &amp; Collins, 2010.) Despite the potential advantages of vast EHR data available, constraints of privacy and legislation hinder its use (Rieke et al., 2020.) Health data exists in an interconnected healthcare system ...
master thesis 2024
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Li, Martin (author)
In recent years, the rapid advancements in big data, machine learning, and artificial intelligence have led to a corresponding rise in privacy concerns. One of the solutions to address these concerns is federated learning. In this thesis, we will look at the setting of vertical federated learning based on tree models. We have built a system that...
master thesis 2024
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Li, Qiongxiu (author), Gundersen, Jaron Skovsted (author), Lopuhaa-Zwakenberg, Milan (author), Heusdens, R. (author)
Privacy-preserving distributed average consensus has received significant attention recently due to its wide applicability. Based on the achieved performances, existing approaches can be broadly classified into perfect accuracy-prioritized approaches such as secure multiparty computation (SMPC), and worst-case privacy-prioritized approaches...
journal article 2024
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Musick, Geoff (author), Duan, Wen (author), Najafian, S. (author), Sengupta, Subhasree (author), Flathmann, Christopher (author), Knijnenburg, Bart (author), McNeese, Nathan (author)
Newly-formed teams often encounter the challenge of members coming together to collaborate on a project without prior knowledge of each other’s working and communication styles. This lack of familiarity can lead to conflicts and misunderstandings, hindering effective teamwork. Derived from research in social recommender systems, team...
journal article 2024
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Li, T. (author), Xu, L. (author), Erkin, Z. (author), Lagendijk, R.L. (author)
With the fast development of e-commerce, there is a higher demand for timely delivery. Logistic companies want to send receivers a more accurate arrival prediction to improve customer satisfaction and lower customer retention costs. One approach is to share (near) real-time location data with recipients, but this also introduces privacy and...
conference paper 2024
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Spanninga, Paulien (author)
In recent years, the medical world has seen rapid digitalisation. Digitalisation of healthcare and the opportunities of remote monitoring can help to keep the healthcare system affordable and accessible. A promising application of remote monitoring is the use of consumer-grade wearables for clinical care. However, vulnerabilities leave consumer...
master thesis 2023
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Agahari, W. (author)
Data sharing through data marketplaces, which rely on a Trusted Third Party (TTP), can benefit businesses and society. However, many companies and consumers are increasingly reluctant to share data due to mounting concerns over data control and privacy. Emerging privacy-enhancing technologies (PETs) like Multi-Party Computation (MPC), which...
doctoral thesis 2023
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van Assen, Jorrit (author)
Recent developments in the capability and availability of small internet of things devices has meant that networked medical devices, like networked implants and wearable monitors, have become more widespread. This data is invaluable for solving pressing global healthcare concerns, like eectively monitoring and treating heart patients. The...
master thesis 2023
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Humblet Vertongen, Marie (author)
Face recognition using lidar presents challenges arising from high dimensionality and data sparsity, especially at longer distances. This paper proposes a novel approach for face recognition via automotive lidar. The approach leverages a combination of deep learning and point cloud processing techniques. After identification of the facial point...
master thesis 2023
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Kroskinski, Ivo (author)
Organizations use cloud service providers for outsourcing their data, since this includes advantages such as: scalability, security and no need for in house experts. Therefore, outsourcing data to cloud providers results in reduced costs. <br/>The disadvantage of outsourcing data to a cloud provider, is that organizations are not in control of...
master thesis 2023
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Trap, Cyril (author)
Privacy is a human right, yet, people’s behavior on the web is constantly tracked. Tor, an anonymity network, is an effective defence against tracking. However, Tor’s multiplexing of logically independent data streams into a single TCP connection causes issues. Tor with QUIC has been implemented as an alternative with better performance but it...
master thesis 2023
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Samardžić, Mariana (author)
The Machine Learning (ML) technology has taken the world by storm since it equipped the machines with previously unimaginable decision-making capabilities. However, building powerful ML models is not an easy task, but the demand for their utilization in different industries and areas of expertise is high. This was recognized by entities that...
master thesis 2023
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