DETEKSI SMURF DDOS PADA JARINGAN SOFTWARE DEFINED NETWORK MENGGUNAKAN METODE NAIVE BAYES

Published on Dec 21, 2019
Syukran Rizki , Deris Stiawan10
Estimated H-index: 10
,
Ahmad Heryanto3
Estimated H-index: 3
Source
Abstract
In this study, the authors detected using the Naive Bayes method for distributed smurf attack (DDoS) on a software defined network (SDN) implemented in mininet simulations. Smurf Attack is a dos attack by sending an icmp request packet without a reply from the server. In detecting, it can recognize unique attributes that are considered as attack patterns from smurf ddos such as frame length, icmp type, and icmp identifier. The attack pattern is used as a detecting parameter in detecting using the Naive Bayes method. The scenario uses six hosts, three hosts as attackers, two hosts as clients and one host as a server running http services. The results of tests that have been carried out by detecting using the Naive Bayes method will be compared with the Snort Intrusion detection System, the Naive Bayes method has a 99.96% accuracy presentation while the IDS snort has an accuracy of 99.99%.
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