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Vehicle classification using inductive loops sensors
Halachkin, Aliaksei ; Klečka, Jan (referee) ; Honec, Peter (advisor)
This project is dedicated to the problem of vehicle classification using inductive loop sensors. We created the dataset that contains more than 11000 labeled inductive loop signatures collected at different times and from different parts of the world. Multiple classification methods and their optimizations were employed to the vehicle classification. Final model that combines K-nearest neighbors and logistic regression achieves 94\% accuracy on classification scheme with 9 classes. The vehicle classifier was implemented in C++.
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System for Detection of APT Attacks
Hujňák, Ondřej ; Kačic, Matej (referee) ; Barabas, Maroš (advisor)
The thesis investigates APT attacks, which are professional targeted attacks that are characterised by long-term duration and use of advanced techniques. The thesis summarises current knowledge about APT attacks and suggests seven symptoms that can be used to check, whether an organization is under an APT attack. Thesis suggests a system for detection of APT attacks based on interaction of those symptoms. This system is elaborated further for detection of attacks in computer networks, where it uses user behaviour modelling for anomaly detection. The detector uses k-nearest neighbors (k-NN) method. The APT attack recognition ability in network environment is verified by implementing and testing this detector.
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Vehicle classification using inductive loops sensors
Halachkin, Aliaksei ; Klečka, Jan (referee) ; Honec, Peter (advisor)
This project is dedicated to the problem of vehicle classification using inductive loop sensors. We created the dataset that contains more than 11000 labeled inductive loop signatures collected at different times and from different parts of the world. Multiple classification methods and their optimizations were employed to the vehicle classification. Final model that combines K-nearest neighbors and logistic regression achieves 94\% accuracy on classification scheme with 9 classes. The vehicle classifier was implemented in C++.
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System for Detection of APT Attacks
Hujňák, Ondřej ; Kačic, Matej (referee) ; Barabas, Maroš (advisor)
The thesis investigates APT attacks, which are professional targeted attacks that are characterised by long-term duration and use of advanced techniques. The thesis summarises current knowledge about APT attacks and suggests seven symptoms that can be used to check, whether an organization is under an APT attack. Thesis suggests a system for detection of APT attacks based on interaction of those symptoms. This system is elaborated further for detection of attacks in computer networks, where it uses user behaviour modelling for anomaly detection. The detector uses k-nearest neighbors (k-NN) method. The APT attack recognition ability in network environment is verified by implementing and testing this detector.
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Okrajový jev v mnohorozměrných datech
Jiřina, Marcel ; Jiřina jr., M.
In this paper we show some strange features of multidimensional data and their influence on classification. We introduce the probability distribution mapping function, and the distribution density mapping function which maps probability density distribution of points in n-dimensional space to a similar distribution in one-dimensional space of distances. The power approximation of the probability distribution mapping function is introduced and an application for a probability density estimation including the boundary effect in high dimensions is shown. Some results obtained with the new method for classification are shown.
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