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Network Anomaly Detection
Lieskovan, Tomáš ; Blažek, Petr (referee) ; Hajný, Jan (advisor)
This semester project presents an analysis of network traffic and detection of anomalies in network traffic by several various means. In the first part of the paper there is an explanation of the methods aiming at denial of service. Then in the second part an implementation of protection by means of selected solutions is presented. The intent is to compare these means which are supposed to detect cyber attacks aiming at denial of service. Another intent is to choose the best solutions from the categories of open-source and commercial solutions. The target of the master thesis was to work out a comparison between actual solutions for detection of DoS and DDoS attacks.
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Behavioral Analysis of Network Traffic and (D)DoS Attack Detection
Chapčák, David ; Hajný, Jan (referee) ; Malina, Lukáš (advisor)
The semestral thesis deals with the analysis of the modern open-source NIDPS tools for monitoring and analyzing the network traffic. The work rates these instruments in terms of their network location and functions. Also refers about more detailed analysis of detecting and alerting mechanisms. Further analyzes the possibilities of detection of anomalies, especially in terms of statistical analysis and shows the basics of other approaches, such as approaches based on data mining and machine learning. The last section presents specific open-source tools, deals with comparison of their activities and the proposal allowing monitoring and traffic analysis, classification, detection of anomalies and (D)DoS attacks.
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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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Optimalization recommendations for internet sales of Triola company
Dvořáková, Ivana ; Barton, Monika (advisor) ; Dohnal, Petr (referee)
This diploma thesis demonstrates the importance of the internet sales in today's world, using an example of the real world company, Triola, which specializes in lingerie manufacturing. Objective of this thesis is behavioral analysis of the company's customers, followed by evaluation of this knowledge which results into recommendations on how to optimize internet sales and how to enhance the design and functionality to achieve this. Analysis and its evaluation are both based on the latest research in this field, which describes the customer's motivation for the internet shopping and the correlation between web design and impulsive shopping. Part of the analysis is also the comparison of trends in behavior of customers all across the world with customers from Czech Republic and with customers of Triola company, trying to identify trends that will likely affect the Triola company in the future. The thesis also comes up with important information about the customers of the Triola company and possible evolution of the internet sales and shows the different approaches for the Triola to take, in order to make internet shopping a pleasant experience for its customers and to raise the internet sales rates as a result.
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