Essays about: "anomali detektion"
Found 5 essays containing the words anomali detektion.
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1. Evaluating Unsupervised Methods for Out-of-Distribution Detection on Semantically Similar Image Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Out-of-distribution detection considers methods used to detect data that deviates from the underlying data distribution used to train some machine learning model. This is an important topic, as artificial neural networks have previously been shown to be capable of producing arbitrarily confident predictions, even for anomalous samples that deviate from the training distribution. READ MORE
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2. Anomaly Detection using LSTM N. Networks and Naive Bayes Classifiers in Multi-Variate Time-Series Data from a Bolt Tightening Tool
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : In this thesis, an anomaly detection framework has been developed to aid in maintenance of tightening tools. The framework is built using LSTM networks and gaussian naive bayes classifiers. The suitability of LSTM networks for multi-variate sensor data and time-series prediction as a basis for anomaly detection has been explored. READ MORE
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3. Unsupervised real-time anomaly detection on streaming data for large-scale application deployments
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Anomaly detection is the classification of data points that do not adhere to the familiar pattern; in previous studies there existed a need for extensive human interactions with either labelling or sorting normal and abnormal data from one another. In this thesis, we want to go one step further and apply machine learning techniques on time-series data in order to have a deeper understanding of the properties of a given data point without any sorting and labelling. READ MORE
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4. A Multivariate Data Stream Anomaly Detection Framework
University essay from KTH/Skolan för elektro- och systemteknik (EES)Abstract : High speed stream anomaly detection is an important technology used in many industry applications such as monitoring system health, detecting financial fraud, monitoring customer's unusual behavior and so on. In those scenarios multivariate data arrives in high speed, and needs to be calculated in real-time. READ MORE
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5. Near Real-time Detection of Masquerade attacks in Web applications : catching imposters using their browsing behavor
University essay from KTH/KommunikationsnätAbstract : This Thesis details the research on Machine Learning techniques that are central in performing Anomaly and Masquerade attack detection. The main focus is put on Web Applications because of their immense popularity and ubiquity. This popularity has led to an increase in attacks, making them the most targeted entry point to violate a system. READ MORE
