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Anomaly detection by neural networks
Strakoš, Jan ; Sikora, Marek (referee) ; Blažek, Petr (advisor)
This bachelor thesis is focused on anomaly detection represented as computer network attacks by neural network. One of the most common groups of attacks is Distributed Denial of Service (DDoS) attacks, which the system based on neural network should identificate. In the theoretical part of this thesis are described legitimate, non-standard and illegitimate traffic. Another part of this chapter described DDoS attacks, options of their detection, neural networks principle and their use. Practical part describe choosed communication parameters, specifying the threshold intervals of legitimate traffic, constructing a neural network which use of these parameters and threshold intervals, implementation of neural network into the system and presenting results.
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Parametrization of network attacks
Jelínek, Michael ; Sikora, Pavel (referee) ; Blažek, Petr (advisor)
This bachelor thesis is dedicated to the definition of suitable parameters for network attack identification with the use of neural networks. In the theoretical part of this thesis are methods for anomaly detection in network communication, structure of artificial neural networks and DDoS attacks used for verification of detection capabilities. The practical part of this thesis is focused on the process of preparing data, the subsequent implementation into neural networks and a summary of the results achieved for the different setups of neural networks.
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The Typology of Mistakes in Czech to Czech Sign Language Interpreting
Hynková Dingová, Naďa ; Macurová, Alena (advisor) ; Čeňková, Ivana (referee) ; Kučera, Pavel (referee)
This dissertation focuses on the analysis of simultaneous interpreting from Czech into the Czech Sign Language and on mistakes which occur during this process. The terminology the author uses to describe the mistakes is derived from the taxonomy of D. Cokely (1985). Cokely's five types of mistakes in interpreting to a sign language (omissions, additions, substitutions, intrusions and anomalies), including their subtypes were also identified in the analysed texts. The work is based on the analysis of mistakes in the interpreted text, which has confirmed the hypothesis of the thesis stating that the use of free interpreting by Czech Sign Language interpreters is only marginal. The interpreters did not reflect pragmatic aspects of dialogue in an appropriate way and they did not use unique language features of the sign language either. They also heavily relied on the Deaf recipients' knowledge of the majority language. In other parts of the work the author pays attention to other specificities of mistakes made during interpreting into the sign language. These are for example sign deformation, mouth movement during the production of a sign, use of a sign in a context etc. She also focuses on an undesirable "accent", the important elements of which are sign placement, the choice of the sign, rhythm,...
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Detection of anomalies in network traffic using compression methods
Blažek, Libor ; Dvořák, Jan (referee) ; Blažek, Petr (advisor)
The objective of the thesis is to design a practical demonstration of the functionality of selected compression methods. The following chapters will discuss the attacks on terminals and mentioned some measures. The show will be processed using two methods development environment. The attacks will detect anomalies in the network and subsequently carried out at one of the sample data compression methods. Data will be collected as normal operation at the terminal station, and then in the attack.
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Detection of Unusual Events in Temporal Data
Černík, Tomáš ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
Bachelor thesis deals with detection of unusual events (anomalies) in available temporal data. Theoretical part describes existing techniques and algorithms used to detect outliers. There are also introduced meteorological data that are after that used for experimental verification of implemented detection algorithms. Second part, practical one, describes design and implementation of application and algorithms. Algorithms are also tested in search for point, contextual and collective anomalies.
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Knowledge Discovery in Spatio-Temporal Data
Pešek, Martin ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with knowledge discovery in spatio-temporal data, which is currently a rapidly evolving area of research in information technology. First, it describes the general principles of knowledge discovery, then, after a brief introduction to mining in the temporal and spatial data, it focuses on the overview and description of existing methods for mining in spatio-temporal data. It focuses, in particular, on moving objects data in the form of trajectories with an emphasis on the methods for trajectory outlier detection. The next part of the thesis deals with the process of implementation of the trajectory outlier detection algorithm called TOP-EYE. In order to testing, validation and possibility of using this algorithm is designed and implemented an application for trajectory outlier detection. The algorithm is experimentally evaluated on two different data sets.
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Effective Network Anomaly Detection Using DNS Data
Fomiczew, Jiří ; Žádník, Martin (referee) ; Kováčik, Michal (advisor)
This thesis describes the design and implementation of system for effective detection of network anomaly using DNS data. Effective detection is accomplished by combination and cooperation of detectors and detection techniques. Flow data in NetFlow and IPFIX formats are used as input for detection. Also packets in pcap format can be used. Main focus is put on detection of DNS tunneling. Thesis also describes Domain Name System (DNS) and anomalies associated with DNS.
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