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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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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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de Jonge, Bart (author)With the amount of network connected devices every increasing, and many of them running the Secure Shell (SSH) protocol to facilitate remote management, research into SSH attacks is more important than ever. SSH honeypots can be used to act like vulnerable systems while gathering valuable data on the attacker and its methods in the meantime. The...master thesis 2022
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Brussen, Arjen (author)Year after year, the amount of network intrusions and costs associated to them rises. Research in this area is, therefore, of high importance and provides valuable insight in how to prevent or counteract intrusions. Machine learning algorithms seem to be a promising answer for automated network intrusion detection, as their results often reach...master thesis 2021
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van Hal, Sven (author)The cyber arms race has red and blue teams continuously at their toes to keep ahead. Increasingly capable cyber actors breach secure networks at a worrying scale. While network monitoring and analysis should identify blatant data exfiltration attempts, covert channels bypass these measures and facilitate surreptitious information extraction. The...master thesis 2021
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Bilstra, Cas (author)Machine learning models are increasing in popularity and are nowadays used in a wide range of critical applications in fields such as Automotive, Aviation and Medical. Among machine learning models, tree ensemble models are a popular choice due to their competitive performance and high degree of explainability. Like most machine learning models...master thesis 2021
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Simidžioski, Maria (author)Adversarial attacks pose a risk to machine learning (ML)-based network intrusion detection systems (NIDS). In this manner, it is of great significance to explore to what degree these methods can be viably utilized by potential adversaries. The majority of adversarial techniques are designed for unconstrained domains such as the image recognition...master thesis 2021