Detection and Classification of DDos Attack on Software Defined Network

Irma Anggraeni, Dinar Munggaran Akhmad

Abstract


Software-Defined Networking (SDN) is a new network paradigm that changes network architecture. However, it turns out that the SDN network also has several issues, one of which is security. The higher the traffic on the network, the higher the possibility of security threats that will occur. Therefore, it is necessary to detect attacks that might occur on this SDN network. This study will detect attacks on the SDN network with the stages carried out, namely the process of building an SDN architecture using a mininet emulator, then network simulation according to the topology, retrieval of traffic data using wireshark and performing data analysis using the Weka application on the NSL KDD dataset. The results of this research found that a DDos attack a ping of death is an attack that sends messages continuously to the recipient, causing the computer to crash, then analysis of attack classification data is carried out using a dataset to compare machine learning algorithms that have high accuracy was Random Forests. The targeted output in this research is published in the Journal of Computing.


Keywords


Network attacks; NSL KDD ;Software Defined Network (SDN

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