Detection and mitigation of cyber attacks at local area networks

The bachelor thesis is focused on the detection and mitigation of flood attacks in local area networks. The thesis can be divided into two parts. In the theoretical part, first flooding attacks are described. Then, the problem of attack detection is discussed in depth, including the implemented detection methods. Subsequently, the classification of detection tools by location is discussed and examples of detection tools are given. The last theoretical section is devoted to network mapping methods and topology detection tools. In the practical part, the design of the IDS and the test network is discussed. The network consists of three end devices namely: the IDS, the victim and the attacker. A Mikrotik router is used to ensure connectivity between all the devices. The IDS has been implemented in Python and is composed of individual modules that extend its functionality. The most important module is the detection module, which contains detection methods against SYN Flood, UDP Flood, ICMP Flood attacks and one universal comprehensive method against all flood attacks. The ARP Scan module allowed the IDS to map the network and use ARP queries to detect the presence of endpoint devices in the network. The learning module made it easier to set up rules for each detection method by monitoring network traffic over a period of time. It then determines appropriate rule values from the detected data. The SSH module provided IDS with the ability to proactively respond to attacks and disconnect the attacker from the rest of the network. ARP Scans also use the SSH module to discover information about guests. The IDS has been tested in both virtual and real environments. The results show that the developed detection methods work and the IDS can stop the attack in a reasonable time. ARP Scanning was also tested and was able to detect new guests on average in the first pass. The effect of IDS on communication was also monitored and found to be minimal