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Presekal, A. (author), Stefanov, Alexandru (author), Subramaniam Rajkumar, Vetrivel (author), Palensky, P. (author)The cyber attacks in Ukraine in 2015 and 2016 demonstrated the vulnerability of electrical power grids to cyber threats. They highlighted the significance of Operational Technology (OT) communication-based anomaly detection. Many anomaly detection methods are based on real-time traffic monitoring, i.e., Intrusion Detection Systems (IDS) that may...conference paper 2023
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Jiménez Rios, Alejandro (author), Plevris, Vagelis (author), Nogal Macho, M. (author)Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently evidenced by the collapse of several bridges worldwide. The objective of this systematic review is to collect and synthesize state-of-the-art knowledge and information...review 2023
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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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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
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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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Phusakulkajorn, W. (author), Hendriks, J.M. (author), Moraal, J. (author), Dollevoet, R.P.B.J. (author), Li, Z. (author), Nunez, Alfredo (author)In this paper, a fuzzy interval-based method is proposed for solving the problem of rail defect detection relying on an on-board measurement system and a multiple spiking neural network architecture. Instead of outputting binary values (defect or not defect), all data will belong to both classes with different spreads that are given by two fuzzy...conference paper 2022
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Cao, C.S. (author), Blaise, Agathe (author), Verwer, S.E. (author), Rebecchi, Filippo (author)These days more companies are shifting towards using cloud environments to provide their services to their client. While it is easy to set up a cloud environment, it is equally important to monitor the system's runtime behaviour and identify anomalous behaviours that occur during its operation. In recent years, the utilisation of Recurrent...conference paper 2022
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Wang, H. (author), Hendriks, J.M. (author), Dollevoet, R.P.B.J. (author), Zoeteman, Arjen (author), Nunez, Alfredo (author)Aiming to handle the increasing variety and volume of railway infrastructure monitoring data, this paper explores the use of intelligent data fusion methods for automatic anomaly detection of railway catenaries. Three classical data dimensionality reduction methods, namely the principal component analysis (PCA), the autoencoder neural network,...conference paper 2022
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Hajee, Bram (author), Wisse, Kees (author), Mohajerin Esfahani, P. (author)Multi-sensor networks are becoming more and more popular in order to assess the post-occupancy performance of smart buildings, since they enable continuous monitoring with a high spatial resolution of the occupancy, thermal comfort and indoor air quality. An urgent, but poorly attended topic in this field is the automated detection of sensor...conference paper 2022
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Pan, K. (author), Palensky, P. (author), Mohajerin Esfahani, P. (author)The main objective of this article is to develop scalable dynamic anomaly detectors with high-fidelity simulators of power systems. On the one hand, models in high-fidelity simulators are typically 'intractable' if one opts to describe them in a mathematical formulation in order to apply existing model-based approaches from the anomaly...journal article 2022
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Hu, F. (author), van Leijen, F.J. (author), Chang, L. (author), Wu, Jicang (author), Hanssen, R.F. (author)Synthetic aperture radar (SAR) missions with short repeat times enable opportunities for near real-time deformation monitoring. Traditional multitemporal interferometric SAR (MT-InSAR) is able to monitor long-term and periodic deformation with high precision by time-series analysis. However, as time series lengthen, it is time-consuming to...journal article 2022
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de Gijsel, Stefan L. (author), Vijn, A.R.P.J. (author), Tan, Reinier G. (author)This paper proposes an algorithm to localize a magnetic dipole using a limited number of noisy measurements from magnetic field sensors. The algorithm is based on the theory of compressed sensing, and exploits the sparseness of the magnetic dipole in space. Beforehand, a basis consisting of magnetic dipole fields belonging to individual...journal article 2022
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Herrera Semenets, V. (author), Hernández-León, Raudel (author), Bustio-Martínez, Lázaro (author), van den Berg, Jan (author)Telecommunications services have become a constant in people’s lives. This has inspired fraudsters to carry out malicious activities causing economic losses to people and companies. Early detection of signs that suggest the possible occurrence of malicious activity would allow analysts to act in time and avoid unintended consequences. Modeling...conference paper 2022
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Zhang, Qinglong (author), Han, Rui (author), Xin, Gaofeng (author), Liu, Chi Harold (author), Wang, Guoren (author), Chen, Lydia Y. (author)Deep neural networks (DNNs) have been showing significant success in various anomaly detection applications such as smart surveillance and industrial quality control. It is increasingly important to detect anomalies directly on edge devices, because of high responsiveness requirements and tight latency constraints. The accuracy of DNN-based...journal article 2022
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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
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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
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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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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
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Bonifazi, A. (author), Sun, Junzi (author), van Baren, Gerben (author), Hoekstra, J.M. (author)Not all flight data anomalies correspond to operational safety concerns. But anomalous safety events can be linked to anomalies in flight data. During the final phases of a flight, two significant safety events are unstable approach and goaround. In this paper, using Automatic Dependent Surveillance- Broadcast (ADS-B) data, we develop several...conference paper 2021
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Zhao, Weizun (author), Li, L. (author), Alam, Sameer (author), Wang, Yanjun (author)Safety is a top priority for civil aviation. Data mining in digital Flight Data Recorder (FDR) or Quick Access Recorder (QAR) data, commonly referred to as black box data on aircraft, has gained interest for proactive safety management. New anomaly detection methods, primarily clustering methods, have been developed to monitor pilot...journal article 2021