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Models for network flow identification
Smejkalová, Veronika ; Kůdela, Jakub (referee) ; Pavlas, Martin (advisor)
The bachelor thesis is focused on development of a mathematical model of network flow in waste managment. The theoretical part of thesis deals with graph theory, network flow and optimization. The next chapter introduces the mathematical model. The model was compiled with the use of Information systems of waste management. The data are very often burdened by error. The task of the model is revelation of those errors to make the data useful. This thesis also includes suggestions for further development.
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Distributed Tool for Extraction of Information from Network Flows
Sedlák, Michal ; Grégr, Matěj (referee) ; Žádník, Martin (advisor)
This work deals with the extraction of information from flow records that are the result of network monitoring by the IPFIX system. The goal of the work is to design a tool that allows querying stored network flows created by the open-source collector IPFIXcol2. Querying is performed with the highest possible efficiency and performance in mind, which is achieved by using appropriate data structures and thread-level parallelization, as well as by using multiple machines.
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Detection of Malware Communication in Network Flows
Korvas, Václav ; Matoušek, Petr (referee) ; Ryšavý, Ondřej (advisor)
This thesis deals with the issue of network communication of malicious code, methods of their analysis and especially the comparison of accuracy of different machine learning algorithms among themselves. The paper presents a comparison of the accuracy of different machine learning algorithms, both on test data and when used in real life. Accuracy, F1-score and false positive rate were used as metrics to evaluate the results. On the test data, the Random Forest and XGBoost algorithms were found to be the most accurate, achieving 99.2% accuracy with a rate of false positivity of 0.6%. In real-life experiments, approximately 9% of flows were incorrectly detected and classified as malware. When the computer was compromised, the rate of flows classified as malware increased to 18%, and several indicators of compromise were captured and confirmed the infection of the computer.
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Optimization in transportation problems
Brandstetter, Matyáš ; Mrázková, Eva (referee) ; Popela, Pavel (advisor)
The thesis deals with optimization models in transportation problems. It begins with a brief introduction to graph theory, linear programming and network flows. The text is accompanied with pictures made in GeoGebra. The presented problems are explained with particular examples. Transportation problems in network flows and their Python implementation recieve more attention in throughout the thesis. Functions written in Python help with data preprocessing and preparation, that is needed in order to solve larger optimization problems.
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Selected Advanced Stochastic Programming Models
Brzobohatý, Jan ; Hrabec, Dušan (referee) ; Popela, Pavel (advisor)
This diploma thesis deals with stochastic dominance. The goal is to lay the foundations for defining stochastic dominance, to describe its properties and to explain this concept on simple examples. Another goal is to apply this concept to network problems with random price. Examples in this thesis also contain solutions and python code how to find them.
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Advanced Optimization of Network Flows
Cabalka, Matouš ; Hrabec, Dušan (referee) ; Popela, Pavel (advisor)
The master’s thesis focuses on the optimization models in logistics with emphasis on the network interdiction problem. The brief introduction is followed by two overview chapters - graph theory and mathematical programming. Important definitions strongly related to network interdiction problems are introduced in the chapter named Basic concepts of graph theory. Necessary theorems used for solving problems are following the definitions. Next chapter named Introduction to mathematical programming firstly contains concepts from linear programming. Definitions and theorems are chosen with respect to the following maximum flow problem and the derived dual problem. Concepts of stochastic optimization follow. In the fifth chapter, we discuss deterministic models of the network interdiction. Stochastic models of the network interdiction follow in the next chapter. All models are implemented in programmes written in the programming language GAMS, the codes are attached.
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IP Flow Filter
Štoffa, Imrich ; Krobot, Pavel (referee) ; Wrona, Jan (advisor)
This thesis is focused on unification of filtering languages used by IP flow collecting program and library for their analysis. At the moment these implementations use different filtering modules and file formats. Because of this, inconsistencies in results arise and as a response to this, creation of one filtering module was proposed as part of effort to better integrate collection and analysis of IP flows using these programs. The one filtering module aims to provide one implementation and support for popular filtering language for use in the programs. Thesis contains theoretical introduction to flow monitoring in networks, describes algorithms useful for evaluation of conditions on flow records and packets. The core of authors work is design and implementation of the filtering module and its wrappers for the collector and analysis library. Results of performance tests and evaluation of features can be found in the thesis's conclusion.
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Network flows and their modifications
Bitara, Matúš ; Hošek, Jaromír (referee) ; Popela, Pavel (advisor)
The thesis deals with optimization models in transportation problems. Brief introduction to graph theory and linear programming is followed by transportation problem of waste transport. Then there is a part with real data applied to the territory of the Czech Republic. After that the user interface created in Visual Basic programming language is explained. In conclusion computational results are discussed as well as their possible improvement.
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Optimization of rail waste transportation
Ambrozková, Anna ; Hrabec, Dušan (referee) ; Pavlas, Martin (advisor)
The bachelor thesis focuses on optimization of rail waste transportation. Theoretical part is about graph theory and optimization, where is introduced for example representation of graphs, network flows or linear programming. Practical part deals with comparison of road and rail networks, motivational example and at least with the application on real data of whole Czech Republic.
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Stochastic Optimization of Network Flows
Málek, Martin ; Holešovský, Jan (referee) ; Popela, Pavel (advisor)
Magisterská práce se zabývá stochastickou optimalizací síťových úloh. Teoretická část pokrývá tři témata - teorii grafů, optimalizaci a progressive hedging algoritmus. V rámci optimalizace je hlavní část věnována stochastickému programování a dvoustupňovému programování. Progressing hedging algoritmus zahrnuje také metodu přiřazování scénářů a modifikaci obecného algoritmu na dvou stupňové úlohy. Praktická část je věnována modelům na reálných datech z oblasti svozu odpadu v rámci České republiky. Data poskytl Ústav procesního inženýrství.
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