Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Blackhole Attacks in Iot Networks(01. Izmir Institute of Technology, 2020) Sokat, Barış; Ayav, Tolga; Erten, Yusuf MuratIoT technologies are very popular today, and they are used in almost every field. Therefore, the number of IoT devices used is increasing day by day. Like every field in computer networks, security is quite important in IoT networks. However, the resource-constrained nature of IoT devices makes the study of security measures for IoT networks very challenging. In the literature research conducted before this thesis study, it was seen that it can perform a wide variety of RPL-based attacks on IoT networks. One of these attacks is the blackhole attack. Although the black hole attack is functionally simple, the damage it causes in the network can be extremely destructive. As far as it is known, in addition to the limited number of studies in this field of attack, the black hole attack used in the studies in this field has also basic features. The basic feature mentioned here is that the attacker node that will perform a black hole attack drops all the packets that come to it. When the attacker node drops all incoming packets, it causes the topology to change in the network, the number of control messages to increase and the attacker node to be isolated from the network in a short time. However, blackhole attack can be combined with different attacks. Therefore, in this thesis, the node that will perform the black hole attack is designed to allow control messages to pass, while dropping all other packets. Here, it is aimed that the attacker node remains on the network for a longer time. As a result, as long as the attacker node is active, it will be able to drop more packets and the number of control messages in the network will be controlled since the topology does not change. With the black hole attack developed as a result of the simulation tests, the number of control messages released in the network was taken under control and it was observed that the attacker node could remain in the network throughout the simulation period. Thus, the effect of different types of black hole attacks on the network that can be developed has been revealed.Master Thesis Extended Topology Analysis of a Detection Mechanism Implementation Against Botnet Based Ddos Flooding Attack in Sdn(Izmir Institute of Technology, 2019) Karakış, Emre; Erten, Yusuf Murat; Tomur, EmrahWhen SDN comes up as a new technology, while it also brings many benefits such as high availability, scalability and performance, it also brings us new vulnerabilities that is targeted by attackers. Botnet Based DDoS Flooding Attacks have been one of the major problems for service provider networks who encountered these repeatedly since the first DDoS came into existence in the early 2000’s. In this thesis, we mainly concentrate on the source-based detection approach against Botnet Based DDoS Flooding Attack by combining the strength of SDN and s-Flow-RT technology. The main purpose of this research is to detect Botnet Based DDoS Flooding Attack that can also be performed in distributed SDN environments by using a similar approach with an available detection mechanism which is not implemented previously on an extended network with more network elements in order to observe whether the obtained successful results on the small network are compatible with a result obtained on this research. This study also includes a detection application using previously studied detection approach based on statistical inference model. The detection application is tested on virtual environments by organizing a Botnet Based DDoS Flooding Attacks on a predefined source node and then test results show that the mechanism could effectively detect the attack.