This thesis deals with filtering selected DDoS attacks on denial of the service. The the toretical part deals with the problems of general mechanisms used for DDoS attacks, defense mechanisms and mechanisms of detection and filtration. The practical part deals with the filtering of attacks using the iptables and IPS Suricata firewall on the Linux operating system in an experimental workplace using a network traffic generator to verify its functionality and performance, including the statistical processing of output data from filter tools using the Elasticsearch database.

The detection and intrusion prevention systems could be realized as independent hardware or set in the software form on to the host. The primary purpose of these protective elements is the undesirable activity detection such as integrity intrusion of the files, invalid attempts while connecting to the remote service or acquisition of the local network data. The systems react to the event on the basis of the action that is defined by internal rules. We can include the caution sending or communication blocking among possible counteractions. The base principals of the detection and intrusion prevention systems are described in the dissertation. Various types of captured data analyses and processes of the inhere rules creation and further more caution formats are mentioned in the dissertation. There are also considered the alternatives of their location including advantages of selected situations. There is described the installation and setting up of particular elements of the realized network and security systems. In order to the verification of functionality and factor of the protection providing there was realized several selected types of attacks.

Avec l'évolution exponentielle de l'Internet des Objets (IoT), assurer la sécurité des réseaux est devenue un grand défi pour les administrateurs réseaux. La sécurité des réseaux est basée sur de multiples équipements indépendants tels que Firewall, IDS/IPS, NAC dont le rôle principal est de contrôler les informations échangées entre le réseau de l'entreprise et l'extérieur. Or, l'administration de ces équipements peut s'avérer très complexe et fastidieuse si elle est réalisée manuellement, équipement après équipement. L'introduction du concept de Software Defined Networking (SDN) depuis ces dernières années, et du protocole OpenFlow, offre beaucoup d'opportunités pour l'amélioration de la sécurité des réseaux en proposant une administration centralisée et programmable.Dans le cadre de cette thèse, nous avons proposé une nouvelle approche de sécurisation des échanges dans un réseau en fonction des événements détectés et de manière automatisée. Cette solution basée sur l'approche SDN couplé avec un système de détection d'intrusion permet d’analyser, de détecter et de supprimer des menaces de sécurité dans un réseau et de manière automatisée. En implémentant cette solution, nous contribuons à faire évoluer la manière de sécuriser les échanges dans un réseau avec du SDN couplé avec un IDS à travers la mise en place d'une architecture réelle de cas d'usage. Ainsi, la gestion de la sécurité du réseau devient simplifiée, dynamique et évolutive. / With the exponential evolution of the Internet of Things (IoT), ensure the network security has become a big challenge for networkadministrators. Traditionally, the network security is based on multiple independent devices such as firewall, IDS/IPS, NAC where the main role is to monitor the information exchanged between the inside and the outside perimeters of the enterprises networks. However, the administration of these network devices can be complex and tedious with an independent manual configuration. Recently, with the introduction of the Software Defined Networking concept (SDN) and the OpenFlow protocol offers many opportunities by providing a centralized and programmable network administration.As part of this research work, we proposed a new approach to secure the network traffic flows exchanges based on a method of events detection, in an automated manner. This solution is based on the SDN approach coupled to an intrusion detection system which allows analyze, detect and remove security threats. With the implementation, we contribute to change the paradigm of secure the network traffic flows exchanges using the SDN principle, coupled with an IDS in a real use case architecture. In this way, the management of network security becomes simplified, dynamic and scalable.

Master's thesis is focused on intrusion detection for denied of service attacks. These distributed DoS attacks are threat for all users on the Internet, so there is deployment of intrusion detection and intrusion prevention systems against these attacks. The theoretical part describes the DoS attacks and its variants used most frequently. It also mentioned variants for detecting DoS attacks. There is also described, which tools are used to detect DDoS attacks most frequently. The practical part deals with the deployment of software tools for detecting DDoS attacks, and create traffic to test detection abilities of these tools.

This diploma thesis is focused on network monitoring. The theoretical part describes using of detection and prevention systems, properties of these systems, their components and detection techniques. Next part of the thesis is focused on EndaceProbe analyzer and analytic application EndaceVision. Also web services, programming language WSDL and protocol SOAP are described. The practical part is focused on creating three laboratory exercises for network monitoring and for using EndaceProbe. Components of the exercises are the traffic generator IXIA and Cisco switches with the application of remote switched port analyzer. There are also used web services EndaceProbe, programming language WSDL and SOAP protocol.

Publication aims to propose and apply new metrics for intrusion detection in network traffic according to analysis of existing metrics, analysis of network traffic and behavioral characteristics of known attacks. The main goal of the thesis is to propose and implement new collection of metrics which will be capable to detect zero day attacks.