Open AccessA Reliable Friedman Hypothesis-Based Detection and Adaptive Load Balancing Scheme for Mitigating Reduction of Quality DDoS Attacks in Cloud Computing
Author(s) -
Vinothkumar Loganathan,
S. Godfrey Winster
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a4127.119119
Subject(s) - denial of service attack , computer science , cloud computing , load balancing (electrical power) , application layer ddos attack , trinoo , computer security , quality of service , distributed computing , computer network , the internet , operating system , geometry , mathematics , grid
The computing resource availability in a cloud computing environment is considered as the vital attribute among the security essentialities due to the consequence of on its on demand service. The class of adversaries related to the Distributed Denial of Service (DDoS) attack is prevalent in the cloud infrastructure for exploiting the vulnerabilities during the implementation of their attack that still make the process of providing security and availability at the same time as a challenging objective. In specific, The in cloud computing is the major threat during the process of balancing security and availability at the same time. In this paper, A Reliable Friedman Hypothesis-based Detection and Adaptive Load Balancing Scheme (RFALBS-RoQ-DDOS) is contributed for effective detection of RoQDDoS attacks through Friedman hypothesis testing. It also inherited an adaptive load balancing approach that prevents the degree of imbalance in the cloud environment. The simulation results of the proposed RFALBS-RoQ-DDoS technique confirmed a superior detection rate and a adaptive load balancing rate of nearly 23% and 28% predominant to the baseline DDoS mitigation schemes considered for investigation.