vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff76572b000000cf3d030001000600 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.
M Arvindhan1, Bhanu Prakash Ande2
Galgotias University, India1, Gambella University, Ethiopia2
DDoS Attacks, EDoS Attacks, Cloud Computing, Machine Learning Detection
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| Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 10 , Issue: 2 , Pages: 2061-2065 )
Date of Publication :
January 2020
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694
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