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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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Shokri Kalisa, Armin (author)
Federated learning allows a multitude of contributors to collaboratively build a deep learning model, all while keeping their individual training data private from one another. However, it is not immune to security flaws such as backdoor attacks in which malevolent adversaries manipulate the global model to trigger specific behaviors. In this...
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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Timmerman, Gerben (author)
This thesis offers a comprehensive exploration of log-based anomaly detection within the domain of cybersecurity incident response. The research describes a different approach and explores relevant log features for language model training, experimentation with different language models and training methodologies, and the investigation of the...
master thesis 2023
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Chen, Congwen (author)
Current backdoor attacks against federated learning (FL) strongly rely on universal triggers or semantic patterns, which can be easily detected and filtered by certain defense mechanisms such as norm clipping, comparing parameter divergences among local updates. In this work, we propose a new stealthy and robust backdoor attack with flexible...
master thesis 2023
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Xu, Cassie (author)
Malware poses a serious security risk in today’s digital environment. The defense against malware mainly relies on proactive detection. However, antivirus products often fail to detect new malware when the signature is not yet available. In the event of a malware infection, the common remediation strategy is reinstalling the system. However, the...
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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Thomas, Wessel (author)
Network Intrusion Detection Systems (NIDSs) defend our computer networks against malicious network attacks. Anomaly-based NIDSs use machine learning classifiers to categorise incoming traffic. Research has shown that classifiers are vulnerable to adversarial examples, perturbed inputs that lead the classifier into misclassifying the input....
master thesis 2023
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Verboom, Bram (author)
Software is everywhere, and going back to a life without software is unimaginable. Unfortunately, software does not always behave as expected, even though during the development cycle, software is usually tested to verify its correctness. To aid in testing, methods such as fuzzing or symbolic execution are used for automatic verification...
master thesis 2023
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Elgar, Peter (author)
RSA encryption standard is a vital component of everyday internet communication. It is currently seen as being unbreakable as the problem that it is based on, semiprime factorisation, is an NP problem. Therefore, to try and break RSA using the current state of the art factoring method will take thousands of years. However, thanks to the advent...
master thesis 2022
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Houtman, Marco (author)
Established research that is done on finding similarities between two finite automata, or finite state machines, is based on matching symbols that are shared between the two automata. In our research, we define a scenario in which the shared alphabet is either partially or completely obscured due to translations. We emulate a scenario where 2...
master thesis 2022
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Serné, Luke (author)
In recent years, computers have found their way into nearly every part of life. This led to the creation of many embedded devices, which are usually quite different from the more commonly known computers and each other. The cause of this is the diversity in constraints that are placed on these devices, in terms of size, weight, energy...
master thesis 2022
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Kloppenburg, Mayke (author)
Nowadays, software is an integral part of many companies. However, the codebase can grow large and complicated and is often insufficiently documented. To gain insight, tools have been made to infer state machines and process models from software logs. These tools produce different types of models such as automata and Petri nets. The main...
master thesis 2022
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Nguyen, Charlie (author)
Over the past centuries, cybercrime has constantly grown. Among the most popular attacks against companies are phishing emails that especially gained popularity for threat actors to use as a tool during the COVID-19 pandemic. By changing the working environment, most communication channels between employees shifted from personal conversations...
master thesis 2022
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Mouwen, Dennis (author)
Every day, Intrusion Detection Systems around the world generate huge amounts of data. This data can be used to learn attacker behaviour, such as Techniques, Tactics, and Procedures (TTPs). Attack Graphs (AGs) provide a visual way of describing these attack patterns. They can be generated without expert knowledge and vulnerability reports. The...
master thesis 2022
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Veraart, Maartje (author)
The rise of alarming cyber breaches and cyber security attacks is causing the world to consider the security of our cyber space. A Security Operations Center (SOC) is a center where the security of a company is monitored to prevent cyber breaches. Security analysts in the SOC examine alerts that come from different devices and analyse what is...
master thesis 2022
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