Review of detection DDOS attack detection using naive bayes classifier for network forensics

45Citations
Citations of this article
106Readers
Mendeley users who have this article in their library.

Abstract

Distributed Denial of Service (DDoS) is a type of attack using the volume, intensity, and more costs mitigation to increase in this era. Attackers used many zombie computers to exhaust the resources available to a network, application or service so that authorized users cannot gain access or the network service is down, and it is a great loss for Internet users in computer networks affected by DDoS attacks. This research proposed to develop a new approach to detect DDoS attacks based on network traffic activity were statistically analyzed using Gaussian Naive Bayes method. Data will be extracted from training and testing of network traffic in a core router at Master of Information Technology Research Laboratory Ahmad Dahlan University Yogyakarta (MITRLADUY). The new approach in detecting DDoS attacks is expected to be a relation with Intrusion Detection System (IDS) to predict the existence of DDoS attacks based on average and standard deviation of network packets in accordance with the Gaussian method.

Cite

CITATION STYLE

APA

Fadlil, A., Riadi, I., & Aji, S. (2017, June 1). Review of detection DDOS attack detection using naive bayes classifier for network forensics. Bulletin of Electrical Engineering and Informatics. Institute of Advanced Engineering and Science. https://doi.org/10.11591/eei.v6i2.605

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free