Cloud computing is the cutting edge and has become inevitable in all forms of computing. This is due to its nature of elasticity, cost-effectiveness, availability, etc. The online applications like e-commerce, and e-healthcare applications are moving to the cloud to reduce their operational cost. These applications have the vulnerability of a HTTP flooding Distributed Denial of Service attack in the cloud. This flooding attack aims to overload the application, making it unable to process genuine requests and bring it down. So, these applications need to be secured and safeguarded against such attacks. This HTTP flooding attack is one of the key challenging issues as it shows normal behaviour with regard to all lower networking layers like TCP 3-way handshaking by mimicking genuine requests and it is even harder in the cloud due to the cloud properties. This article offers a solution for detecting a HTTP flooding attack in the cloud by using the novel TriZonal Linear Prediction (TLP) model. The solution was implemented using OpenStack and the FIFA Worldcup '98 data set for experimentation.
Noise-Robust Multilayer Perceptron Architecture for Distributed Denial of Service Attack Detection
