The objective of this work is focused on trains and their role in integrated transport systems. The functionality of public train transport is shown on 2 most developped integrated systems in Czech republic. My work include comparison of these 2 systems and the role of trains in both of them.

This This Master´s Thesis deals with the problems of the integrated transport system in the South Bohemian Region. After the explanation of the concept the integrated transport system follows the specification of the transport systems, the transport divisions and short introduction with the legislative framework. Further in my Master´s thesis I describe two chosen efficient and sophisticated integrated transport systems in the Czech Republic. Next part of this work deals with the current traffic situation in the South Bohemian Region. It follows the prices comparison for the tickets in the local transport and analysis the connection in chosen towns in the South Bohemian Region. The aim of this work is to make a suggestion of the integrated transport system, chose the model, tariffs and prices for the tickets. In the last part of this work I pay attention to the detected weaknesses and I suggest their possible solution.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第22573号 / 情博第710号 / 新制||情||122(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 岡部 寿男, 教授 森 信介, 教授 五十嵐 淳 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

This paper deals with a problem of detection of network traffic anomaly and classification of network flows. Based on existing methods, paper describes proposal and implementaion of a tool, which can automatically classify network flows. The tool uses CUDA platform for network data processing and computation of network flow metrics using graphics processing unit. Processed flows are subsequently classified by proposed methods for network anomaly detection.

This student work focuses on security against network attacks. It focus on network attacks and ways to prevent them. Subsequently, it deals with the Snort variant of the IPS/IDS system. It deal with the connection between Mikrotik and the Snort Linux server

Diploma thesis deals with monitoring critical infrastructure, critical information infrastructure and network monitoring in energetic industry. The goal is to create analytical environment for processing logs from the network, to map the most critical segments of the network and implementation of monitoring and network devices, that increase security and mitigate risks of security events or security incidents

This work describes security mechanisms of wireless network based on 802.11 standard and security enhancement 802.11i of these networks known as WPA2, where the analysis of vulnerabilities and attacks on these networks were performed. The work discusses two major security issues. The first is unsecure management frames responsible for vulnerability with direct impact on availability and the other is the vulnerability that allows executing the impersonalize type of attacks. The system for generation attacks was designed to realize any attack very fast and efficient. The core of the thesis is the design of a system for attack analysis using the principle of trust and reputation computation. The conclusion of the work is devoted to experimenting with the proposed system, especially with the selection of suitable metrics for calculating the trust value.

This diploma thesis is focused on problematics of the industrial networks and offered security by the industrial protocols. The goal of this thesis is to create specific methods for detection of security incidents. This thesis is mainly focused on protocols Modbus/TCP and DNP3. In the theoretical part, the industrial protocols are described, there are defined vectors of attacks and is described security of each protocol. The practical part is focused on the description and simulation of security incidents. Based on the data gathered from the simulations, there are identified threats by the introduced detection methods. These methods are using for detecting the security incident an abnormality in the network traffic by created formulas or machine learning. Designed methods are implemented to IDS (Intrusion Detection System) of the system Zeek. With the designed methods, it is possible to detect selected security incidents in the destination workstation.

The work's main topic is a recently published slow DoS attack called SlowDrop. The work focuses on the subject of describing the current state of the DoS problem as a whole and the SlowDrop attack as well. It works with this theoretical basis during the implementation of it's own SlowDrop attack model. This model is tested in various scenarios and the outcome results are analyzed and constructively discussed. Furthermore defensive mechanisms against this threat and DoS attacks in general are proposed, specific methods shown and configurations recommended. These methods are followingly tested and evaluated. Last but not least the traffic of a SlowDrop attacker and a legitimate client with bad connection, which the SlowDrop attack is trying to immitate, are compared. From this comparison final conclusions of this work are drawn.

The diploma thesis is focused on the detection of a slow DoS attack named SlowDrop. The attack tries to imitate a legitimate person with a slow internet connection and does not show a new strong signature, so the attack is difficult to detect. The diploma thesis is based on the work of Ing. Mazanek in which the SlowDrop attack script was created. At the theoretical level, the issue of DoS attacks is described in general, but also in particular. Furthermore, the work develops methods for solving the problem of SlowDrop attack detection. The methods are then defined in detail and tested in a simulation environment. The practical part describes data analysis, signature detection, anomaly detection using neural networks and a detection script. In all practical parts, the used technologies and solution procedures are described in detail. The specific implementation of the solution and the achieved results are also presented. Finally, the individual results are evaluated, compared individually, but also among themselves. The obtained results show that the attack is detectable using a neural network and by created detection script.