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Song, Yuqian (author)
In the digital age, the proliferation of personal data within databases has made them prime targets for cyberattacks. As the volume of data increases, so does the frequency and sophistication of these attacks. This thesis investigates database security threats by deploying open source database honeypots to gather threat intelligence. We utilized...
master thesis 2024
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Koursiounis, Giorgos (author)
<div>Security researchers and industry firms employ Internet-wide scanning for information collection, vulnerability detection and security evaluation, while cybercriminals make use of it to find and attack unsecured devices. Internet scanning plays a considerable role in threat detection &amp; response, and cyber threat intelligence. We adopt a...
master thesis 2024
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te Marvelde, Pepijn (author)
In the realm of machine learning (ML), the need for efficiency in training processes is paramount. The conventional first step in an ML workflow involves collecting data from various sources and merging them into a single table, a process known as materialization, which can introduce inefficiencies caused by redundant data. Factorized ML strives...
master thesis 2024
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Chen, Ivo (author)
Large language models (LMs) are increasingly used in critical tasks, making it important that these models can be trusted. The confidence an LM assigns to its prediction is often used to indicate how much trust can be placed in that prediction. However, a high confidence can be incorrectly trusted if it turns out to be incorrect, also known as a...
master thesis 2024
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Eickhoff, Jerrit (author)
Online gaming is the world’s largest entertainment industry by revenue, and supports over 3 billion consumers worldwide. Many of the world’s most popular online games must manage millions of concurrent players through a single unified service. Achieving performant and scalable online games is challenging. Online games are subject to stringent...
master thesis 2024
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Alaka, Shaad (author)
Virtual worlds are rapidly increasing in size, enabled by advancements in computing technology, which puts a large burden on designers creating them.<br/>Procedural Content Generation can help alleviate this burden, though lacks precise control, to the detriment of designer intent. Some PCG algorithms, such as Wave Function Collapse (WFC), known...
master thesis 2023
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Su, Kexin (author)
General-purpose GPUs, renowned for their exceptional parallel processing capabilities and throughput, hold great promise for enhancing the efficiency of data analytics tasks. At the same time, recent developments in query execution engines have integrated the support of OLAP operations in a way that benefits from the zero serialization overhead...
master thesis 2023
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Karatza, Dimitra (author)
The current trend towards the integration of artificial intelligence (AI) and graphics processing unit (GPU) technologies has resulted in the development of embedded hybrid GPU-AI accelerators, which offer high computational power and energy efficiency. One of the key challenges in designing such accelerators is ensuring their timing correctness...
master thesis 2023
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Zelenjak, Jegor (author)
SAGE is an unsupervised sequence learning pipeline that generates alert-driven attack graphs (AGs) without the need for prior expert knowledge about existing vulnerabilities and network topology. Using a suffix-based probabilistic deterministic finite automaton (S-PDFA), it accentuates infrequent high-severity alerts without discarding frequent...
bachelor thesis 2023
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Constantinescu, Vlad (author)
The interpretability of an attack graph is a key principle as it reflects the difficulty of a specialist to take insights into attacker strategies. However, the quantification of interpretability is considered to be a subjective manner and complex attack graphs can be challenging to read and interpret. In this research paper, we propose a new...
bachelor thesis 2023
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Van den Broeck, Senne (author)
Intrusion Detection Systems (IDSes) detect malicious traffic in computer networks and generate a large volume of alerts, which cannot be processed manually. SAGE is a deterministic algorithm that works without a priori network/expert knowledge and can compress these alerts into attack graphs (AGs), modelling intruders’ paths in the network....
bachelor thesis 2023
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Dumitriu, Alexandru (author)
This research paper focuses on the complex domain of alert-driven attack graphs. SAGE is a tool which generates such attack graphs (AGs) by using a suffix-based probabilistic deterministic finite automaton (S-PDFA). One of the substantial properties of this algorithm is to detect infrequent severe alerts while maintaining the context of attacks...
bachelor thesis 2023
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Oprea, Ioan (author)
SAGE is a deterministic and unsupervised learning pipeline that can generate attack graphs from intrusion alerts without input knowledge from a security analyst. Using a suffix-based probabilistic deterministic finite automaton (S-PDFA), the system compresses over 1 million alerts into less than 500 attack graphs (AGs), which are concise and...
bachelor thesis 2023
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Qiu, Jingxuan (author)
Distributed databases often struggle to fulfill their transactional isolation guarantees due to sharding and replication. As a result, the problem of checking isolation levels is consistently receiving attention from academia and industries. Transactional dependency graphs form a useful abstraction to analyze the transactions’ dependencies and...
master thesis 2023
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Kanis, Job (author)
The introduction of cloud hosting has made it possible to elastically provision distributed stream processing systems (SPEs). By dynamically scaling the different operators of the system, resource consumption can be minimised while meeting the system service-level objectives. In the literature, many different auto-scaling techniques are proposed...
master thesis 2023
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Melas, Minas (author)
Data processing systems have become increasingly important in modern computing, as the volume and complexity of data that needs to be analyzed has grown dramatically. Multiple data processing systems have been and are being developed, that are scalable, resilient and performant.<br/><br/>However, despite the advances made in data processing...
master thesis 2023
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Schönfeld, Mariette (author)
Machine learning inference queries are a type of database query for databases where a model pipeline is needed to evaluate its boolean predicates. Using a model zoo it is possible to select a variety of models to execute in a sequence rather than using a highly specialized model to answer every query predicate. Machine learning models can have...
master thesis 2022
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Prins, Nathan (author)
The growing field of research into batteryless or intermittent systems has enabled Internet of Things applications that were previously impossible. For example, the FreeBie system recently introduced Bluetooth Low-Energy (BLE)<br/>to intermittent devices, making medium to long range bi-directional communication a reality for the first time....
master thesis 2022
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Mao, Mao (author)
In real life, the phenomenon of delayed payment of invoices often occurs. Malicious delayed payment may even lead to the break of capital flow of companies. Debtor payment prediction according to the historical payment behaviour of debtors can help give companies more insight into the risk of late payment. The debtor payment prediction is...
master thesis 2022
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Russel, Erwin (author)
Cloud gaming is a new paradigm that allows users to play games in the cloud and stream them to a thin client. While there is little research about cloud gaming, containerization technologies such as Docker could provide a virtualization alternative to Virtual Machines, as these suffer from overhead and GPU pass-through constraints. With Rapture,...
master thesis 2022
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