- document
-
Oerlemans, Carlijn (author)Study objectives: Conventional sleep scoring is based on the scoring criteria of the American Association of Sleep Medicine (AASM) but may not be suited to describe sleep in critically ill children admitted to the Pediatric Intensive Care Unit (PICU). In this study, an anomaly detection model using Gaussian Models trained on sleep stages in data...master thesis 2024
- document
-
Vadachennimalai Selvaraj, Suryaa (author)The Automatic Identification System (AIS) is used in the maritime domain to improve sea traffic safety by requiring vessels to broadcast real-time information such as identity, speed, location, and course. As it allows global monitoring of almost any larger vessel and has the potential to considerably improve vessel traffic services and...master thesis 2023
- document
-
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
- document
-
de Ruijter, Pim (author)The detection of anomalous behaviour is fundamental to component health analysis techniques. However, detecting anomalies is a difficult and time consuming task if their form, location, and frequency are unknown. This research introduces an innovative unsupervised predictive maintenance pipeline that requires minimal domain knowledge and time to...master thesis 2023
- document
-
Rajesh, Aditya (author)The current research work investigates the possibility of using machine learning models to deduce the relationship between WAAM (wire arc additive manufacturing) sensor responses and defect presence in the printed part. The work specifically focuses on three materials from the nickel alloy family – Inconel 718, Invar 36 and Inconel 625, and uses...master thesis 2023
- document
-
Hofman, Daan (author)With the ever-increasing digitalisation of society and the explosion of internet-enabled devices with the Internet of Things (IoT), keeping services and devices secure is becoming more important. Logs play a critical role in sustaining system reliability. Manual analysis of logs has become increasingly difficult, accelerating the development of...master thesis 2023
- document
-
Herrmann, Lars (author)As the volume of telemetry data generated by satellites and other complex systems continues to grow, there is a pressing need for more efficient and accurate anomaly detection methods. Current techniques often rely on human analysis and preset criteria, presenting several challenges including the necessity for expert interpretation and continual...master thesis 2023
- document
-
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
- document
-
Verdoes, Max (author)Chain belt conveyors have become a popular choice for transporting materials in diverse industries. The primary driving force behind these conveyors is the gearmotor, which is composed of an electric motor and a gear unit. The industrial electric motor market is estimated to be 21 billion USD and consumes up to 70\% of the electricity by the...master thesis 2023
- document
-
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
- document
-
Karpova, Natalia (author)Anomaly detection has gathered plenty of attention in the previous years. However, there is little evidence of the fact that existing anomaly detection models could show similar performance on different streaming datasets. <br/>Within this study, we research the applicability of existing anomaly detectors to a wide range of univariate streams....master thesis 2022
- document
-
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
- document
-
Kongurai, Krit (author)State estimation (SE) is a crucial tool for power system state monitoring since the control center requires a process to deal with a large number of imprecise measurements. Several SE methods have been applied and developed for the electric power system in the transmission level in the past several decades. Meanwhile, SE for the distribution...master thesis 2021
- document
-
Huistra, Mark (author)In the fight against money laundering, demand for data-driven Anti-Money Laundering (AML) solutions is growing. Particularly anomaly detection algorithms have proven effective in the detection of suspicious customer behaviour, as well as observing patterns otherwise hidden in customer transaction data. In this thesis, the Isolation Forest...master thesis 2021
- document
-
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
- document
-
de Hoog, Dion (author)In this research, we use different supervised and unsupervised machine learning techniques to detect anomalies in NetFlow data. We aim to create a system for home or small-business use where the user is in control. We use WEKA for the machine learning models and feature selection. The UGR’16 dataset is used to train and test the models. We...master thesis 2021
- document
-
Bonifazi, Alberto (author)This thesis shows that it is possible to produce safety knowledge by mining Automatic Dependent Surveillance-Broadcast (ADS-B) data. The methodology combines exceedance detection and anomaly detection techniques to identify anomalous safety events in approach flights. One of these events is unstable approaches, which are identified with a rule...master thesis 2020
- document
-
Hajee, B. (author)The built environment is becoming healthier, smarter and more energy efficient during the transition to green building activity. Multi-sensor networks are a promising component of this transition, provided that their measurements are reliable. The reliability of the data is a real concern for DWA, as they use it for control purposes as well as...master thesis 2020
- document
-
Ómarsdóttir, Þórunn (author)In this thesis, we study automatically generating explanatory reports for anomalous incidents in a train control system (TCS) using Natural Language Generation (NLG). A TCS is a type of safety-critical software that allows train controllers to correctly set the tracks for a train to pass. The goal of this research is to process the majority of...master thesis 2020
- document
-
Heijne, Yannick (author)Past research has successfully increased the accuracy and quality of horizontal wind speed measurements made by cup anemometers. Errors are introduced in a variety of ways: when operational conditions deviate from calibration, due to flow distortion and as a result of the mechanical properties of an instrument changing during its lifetime....master thesis 2020