Performance Evaluation of Denial of Service Attack Detection in Cloud Computing Environments
V. Saravanan, S. Lekashri, V. Jayasudha, R Ramya, M. Nivedha · 2023
One of the most widely used technologies today, both by developers and end users, is cloud networking. Despite the widespread use of cloud networks, security in the cloud continues to be a crucial research problem and a hotly debated subject. One or more attackers use several compromised nodes to flood a specified target during a denial of service (DoS) assault in the cloud, which renders services unavailable. It is possible to discover the attack characteristics or frequent trends of such denial of service attacks using classification algorithms. In order to identify the Denial of Service attacks, feature selection and classification utilizing deep learning approaches have been applied in this study. This study proposes a novel method for identifying DoS attacks that makes use of the expertise of an authority on the domain. In addition, deep learning algorithm such as Gated Recurrent Units is proposed in this research for Detecting DoS Attacks. In this algorithms, the final classification is carried out and validated on NSL-KDD dataset. The suggested approach is tested on a cloud-based experimental setup, and found that it performed better at detecting DoS attacks than the current security classification methods.