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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
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Habben Jansen, Geert (author)Ever since the invention of the Internet, more and more computers are connected throughout the world. Though this has brought numerous new inventions used every day, like social media, e-commerce, and video conferencing, it also opens up new opportunities for cyber criminals. As the intrusion detection systems used to identify malicious behavior...master thesis 2021
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Fucarev, Silviu (author)Clustering data is a classic topic in the academic community and in the industry. It is by and large one of the most popular unsupervised classification techniques. It is fast and flexible as it can accommodate all kinds of data when a suitable similarity metric is found. SeqClu is an online k-medoids prototype based clustering algorithm...bachelor thesis 2021
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Garack, Jonathan (author)MalPaCa is an unsupervised clustering tool, which the main purpose is to cluster unidirectional network connections based on network behavior. The clustering is only based on non-intrusive (private) packet features such as transport and network header fields, and thus it has a strong potential use-case. This paper focuses on feature extraction...bachelor thesis 2021
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Epifanov, Mikhail (author)Malware Packet-sequence Clustering and Analysis (MalPaCA) is a unsupervised clustering application for malicious network behavior, it currently uses solely sequential features to characterize network behavior. In this paper an extensive comparison between those features and statistical features is performed. During the comparison a better...bachelor thesis 2021
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Al-Obaidi, Rami (author)Clustering is a group of (unsupervised) machine learning algorithms used to categorize data into clusters. The most popular clustering algorithm is k-means clustering. K-means clustering clusters the data into k clusters where a cluster is represented by the mean of the data points called a centroid. Instead of using the mean as a centroid, a...bachelor thesis 2021
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Park, Sung kyung (author)Identifying novel malware and their behaviour enables security engineers to prevent and protect users with devices on the network from attackers. MalPaCA is an algorithm that helps to understand the behaviours of the network traffic by clustering uni-directional network connections which can be analyzed further to interpret which label suites...bachelor thesis 2021
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Hagspiel, Johannes (author)MalPaCa is a novel, unsupervised clustering algorithm, which creates based on the network flow of a software a behavioral profile representing its actual capabilities. One of the key variables affecting is performance and usability is the sequence length or how many packets it analyzes in order to group a connection to a cluster. This article...bachelor thesis 2021
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Moree, Jarno (author)Clustering is a commonly used method in data analysis. It is a complex problem that can be very time consuming, especially when clustering large datasets with many features. Most clustering algorithms scale exponentially in time when increasing the dataset size, making it infeasible to use them for large datasets. Streaming algorithms do not...master thesis 2021