Early Detection of DDoS Attack on Cloud Environment using Queuing Model
A.Saravanan1, S.Sathya bama2
1A.Saravanan, Department of MCA, Sree Saraswathi Thyagaraja College, Pollachi, (Tamil Nadu), India – 642205
2S.Sathya bama, 483, Lawley Road, Coimbatore, (Tamil Nadu), India – 641003
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1624-1631 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2351037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Due to the growth of the internet and related technologies, cloud computing plays the most significant part in providing cost effective services to the user. As the need for the cloud increases, the security issues related to the cloud environment is also increasing dramatically. The main challenge of the cloud environment is in providing quality service, data availability and managing the resources. The intensity of this challenge is increased due to the interruption of the Distributed Denial of Service attack, a most severe vulnerability that causes harm to the cloud environment. Though the attack is not a new risk for the research community, it takes a new dimension in providing a solution for the cloud environment due to its architecture and severe consequences. Due to the growing popularity of cloud computing, the mitigation of various vulnerabilities especially Distributed Denial of Service attack become the ongoing research challenge. In this paper, a framework that prevents and detects the attack at an early stage has been suggested to maintain the availability of cloud resources to its end users. The framework employs screening tests for preventing the cloud environment from Distributed Denial of Service attack. Additionally, the detection algorithm has been suggested that uses a queuing model for detecting the attack. The experimental results show that the proposed method provides a high detection rate.
Keywords: Cloud Computing; Distributed Denial of Service; Detection; Queuing Model; Security Challenge.
Scope of the Article: Probabilistic Models and Methods