DATA MINING APPROACH AND SECURITY OVER DDOS ATTACKS

Abstract
The benefit of on-demand services is one of the most important benefits of using cloud computing; therefore, the payment method in the cloud environment is pay per use. This feature results in a new type of DDOS attack called Economic Denial of Sustainability (EDoS), where as a result of the attack the customer pays the cloud provider extra. Similar to other DDoS attacks, EDoS attacks are divided into different groups, such as bandwidth-consuming attacks, specific target attacks, and connections-layer-exhaustion attacks. In this study, we propose a novel system for detecting different types of EDoS attacks by developing a pro le that learns from normal and abnormal behaviors and classifies them. In this sense, the extra demanding resources are allocated only to VMs that are found to be in a normal situation and thus prevent attack and resource dissemination from the cloud environment.

Authors
M Arvindhan1, Bhanu Prakash Ande2
Galgotias University, India1, Gambella University, Ethiopia2

Keywords
DDoS Attacks, EDoS Attacks, Cloud Computing, Machine Learning Detection
Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 10 , Issue: 2 )
Date of Publication :
January 2020

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.