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Geboers, Sven (author)
Currently, inland waterway shipping mainly includes barges and bulk transportation with little to no variation in volume, product, and route. Since transport over water emits less CO2 per tonne-km than road transport, a potential way to reduce CO2 emissions is to transport more containers via inland waterways. Large delays cause unreliability,...
master thesis 2022
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Li, Qiongxiu (author), Heusdens, R. (author), Christensen, M.T. (author)
Privacy issues and communication cost are both major concerns in distributed optimization in networks. There is often a trade-off between them because the encryption methods used for privacy-preservation often require expensive communication overhead. To address these issues, we, in this paper, propose a quantization-based approach to achieve...
journal article 2022
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Cardaioli, Matteo (author), Conti, M. (author), Tricomi, Pier Paolo (author), Tsudik, Gene (author)
Ideally, secure user sessions should start and end with authentication and de-Authentication phases, respectively. While the user must pass the former to start a secure session, the latter's importance is often ignored or underestimated. Dangling or unattended sessions expose users to well-known Lunchtime Attacks. To mitigate this threat, the...
conference paper 2022
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Li, Meng (author), Zhang, Mingwei (author), Gao, Jianbo (author), Lal, C. (author), Conti, M. (author), Alazab, Mamoun (author)
Location-Based Services (LBSs) depend on a Service Provider (SP) to store data owners’ geospatial data and to process data users’ queries. For example, a Yelp user queries the SP to retrieve the k nearest Starbucks by submitting her/his current location. It is well-acknowledged that location privacy is vital to users and several prominent...
conference paper 2022
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Ofe, H.A. (author), Minnema, Harm (author), de Reuver, G.A. (author)
Purpose: This paper aims to propose a framework for how privacy-preserving technologies (PETs) create business value for organizations. The framework was developed by examining the literature on privacy and information technology’s impact (symbolic and function). The authors evaluate the framework’s applicability using multiparty computation ...
journal article 2022
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Zheng, Yubo (author), Xu, Peng (author), Wang, Wei (author), Chen, Tianyang (author), Susilo, Willy (author), Liang, K. (author), Jin, Hai (author)
Many practical secure systems have been designed to prevent real-world attacks via maximizing the attacking cost so as to reduce attack intentions. Inspired by this philosophy, we propose a new concept named delay encryption with keyword search (DEKS) to resist the notorious keyword guessing attack (KGA), in the context of secure cloud-based...
conference paper 2022
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Xu, Weitao (author), Xue, Wanli (author), Lin, Qi (author), Lan, G. (author), Feng, Xingyu (author), Wei, Bo (author), Luo, Chengwen (author), Li, Wei (author), Zomaya, Albert Y. (author)
Smart space has emerged as a new paradigm that combines sensing, communication, and artificial intelligence technologies to offer various customized services. A fundamental requirement of these services is person identification. Although a variety of person-identification approaches has been proposed, they suffer from several limitations in...
journal article 2022
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Somai, Ashay (author)
This thesis looks at how to characterize weaknesses in machine learning models that are used for detecting privacy-sensitive data in images with the help of crowdsourcing. Before we can come up with a method to achieve a goal, we first need to make clear what we consider privacy-sensitive data. We took the General Data Protection Regulation ...
master thesis 2021
document
Darbari, Shubhankar (author)
The expansion of the Internet and wireless access has led to a widespread increase of Internet of Things applications. These smart devices are becoming a daily aspect of our lives. All the convenient and automated services provided by smart devices come from a centralized service provider. This service provider has access to all the personal...
bachelor thesis 2021
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Ştefan, Andrei (author)
Collaboration is a key technique in modern supply chains, both for building trust with other companies, but also for reducing costs or maximizing profits. It is an approach which provides all involved parties with benefits that they could not possibly achieve on their own. Collaboration, however, requires abundant information, including...
bachelor thesis 2021
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van der Poel, Cesar (author)
Information-Centric Networking (ICN) is a networking paradigm proposed to replace the current IP network. It uses in-network caching to enhance availability. However, as a clean slate approach is unlikely to work, an architecture that allows for the two paradigms to coexist needs to me used to facilitate the transition. Several such...
bachelor thesis 2021
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Arora, Shruti (author)
Information-centric Networking (ICN) is the revolution of the internet due to its many benefit over the current internet infrastructure, namely caching, location-independent routing, and data-centric security. ICN ensures seamless data transfer due to its content-centric nature. Due to its content-centric nature, it is a must to ensure that...
bachelor thesis 2021
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van Tetering, Daphne (author)
The convenient service offered by credit cards and the technological advances in e-commerce have caused the number of online payment transactions to increase daily. With this rising number, the opportunity for fraudsters to obtain cardholder details via online credit card fraud has also increased. As a result, according to the European Central...
master thesis 2021
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Slokom, M. (author), Hanjalic, A. (author), Larson, M.A. (author)
In this paper, we propose a new privacy solution for the data used to train a recommender system, i.e., the user–item matrix. The user–item matrix contains implicit information, which can be inferred using a classifier, leading to potential privacy violations. Our solution, called Personalized Blurring (PerBlur), is a simple, yet effective,...
journal article 2021
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Smith, Marcus (author), Miller, S.R.M. (author)
Biometric facial recognition is an artificial intelligence technology involving the automated comparison of facial features, used by law enforcement to identify unknown suspects from photographs and closed circuit television. Its capability is expanding rapidly in association with artificial intelligence and has great potential to solve crime...
journal article 2021
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Li, Meng (author), Zhu, Liehuang (author), Zhang, Zijian (author), Lal, C. (author), Conti, M. (author), Alazab, Mamoun (author)
E-commerce platforms incorporate reputation systems that allow customers to rate suppliers following financial transactions. Existing reputation systems cannot defend the centralized server against arbitrarily tampering with the supplier’s reputation. Furthermore, they do not offer reputation access across platforms. Rates are faced with privacy...
journal article 2021
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Ho-Sam-Sooi, Nick (author), Pieters, W. (author), Kroesen, M. (author)
Given the significant privacy and security risks of Internet-of-Things (IoT) devices, it seems desirable to nudge consumers towards buying more secure devices and taking privacy into account in the purchase decision. In order to support this goal, this study examines the effect of security and privacy on IoT device purchase behaviour and...
journal article 2021
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Han, Rui (author), Li, Dong (author), Ouyang, Junyan (author), Liu, Chi Harold (author), Wang, Guoren (author), Wu, Dapeng Oliver (author), Chen, Lydia Y. (author)
Deep learning (DL) models are increasingly built on federated edge participants holding local data. To enable insight extractions without the risk of information leakage, DL training is usually combined with differential privacy (DP). The core theme is to tradeoff learning accuracy by adding statistically calibrated noises, particularly to...
journal article 2021
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Dekker, Florine W. (author), Erkin, Z. (author)
Privacy-preserving data aggregation protocols have been researched widely, but usually cannot guarantee correctness of the aggregate if users are malicious. These protocols can be extended with zero-knowledge proofs and commitments to work in the malicious model, but this incurs a significant computational cost on the end users, making adoption...
conference paper 2021
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Dekker, Florine (author)
Privacy-preserving data aggregation protocols have been researched widely, but usually cannot guarantee correctness of the aggregate if users are malicious. These protocols can be extended with zero-knowledge proofs and commitments to work in the malicious model, but this incurs a significant computational cost on the end users, making adoption...
master thesis 2020
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