Essays about: "anomali detektion"

Found 5 essays containing the words anomali detektion.

  1. 1. Evaluating Unsupervised Methods for Out-of-Distribution Detection on Semantically Similar Image Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Magnus Pierrau; [2021]
    Keywords : Out-of-distribution detection; anomaly detection; semantic similarity; image data; comparative evaluation; synthetic image data; Out-of-distribution detektion; anomali detektion; semantisk likhet; bilddata; jämförande utvärdering; syntetisk bilddata;

    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

  2. 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)

    Author : Karl-Filip Selander; [2021]
    Keywords : LSTM; anomaly detection; time-series; multi-variable; sensor; deep learning; LSTM; anomalidetektion; tidsserie; multivariabel; sensor; djupinlärning;

    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

  3. 3. Unsupervised real-time anomaly detection on streaming data for large-scale application deployments

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Carl Jernbäcker; [2019]
    Keywords : ;

    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

  4. 4. A Multivariate Data Stream Anomaly Detection Framework

    University essay from KTH/Skolan för elektro- och systemteknik (EES)

    Author : Jiakun Jin; [2016]
    Keywords : Multivariate; Stream anomaly detection; PYISC; SVM; LOF; DDM; CUSUM; FCWM; Multivariat; ström anomali detektion; PYISC; SVM; LOF; DDM; CUSUM; FCWM;

    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

  5. 5. Near Real-time Detection of Masquerade attacks in Web applications : catching imposters using their browsing behavor

    University essay from KTH/Kommunikationsnät

    Author : Vasileios Panopoulos; [2016]
    Keywords : Naive Bayes; SVM; Support Vector Machines; Machine Learning; IDS; Intrusion Detection System; Web Application; scikit-learn;

    Abstract : 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