|Title: ||DDOS detection using machine learning technique
||Author(s): ||Pande S.
||Keywords: ||DDOS; Machine learning; Network security; NSL-KDD; Ping of death; Random forest
||Abstract: ||Numerous attacks are performed on network infrastructures. These include attacks on network availability, confidentiality and integrity. Distributed denial-of-service (DDoS) attack is a persistent attack which affects the availability of the network. Command and Control (C & C) mechanism is used to perform such kind of attack. Various researchers have proposed different methods based on machine learning technique to detect these attacks. In this paper, DDoS attack was performed using ping of death technique and detected using machine learning technique by using WEKA tool. NSL-KDD dataset was used in this experiment. Random forest algorithm was used to perform classification of the normal and attack samples. 99.76% of the samples were correctly classified.
||Issue Date: ||2021
||Publisher: ||Springer Science and Business Media Deutschland GmbH
||Series/Report no.: ||Vol. 921
|Appears in Collections:||Conference Papers|