Evaluation Model And Integrated Detection Of Flood Attack In Iot Using Artificial Intelligence

Abstract

The Distributed denial of service (DDoS) Attacks are quite difficult to predict and mitigate. The amount of ubiquitous disruption caused by the HTTP flood attack, DNS attacks have caused havoc among users worldwide and uncertainty over the security of their personal data and information. Tools available such as the Golden Eye, LOIC etc. helps to reduce the attack but are not able to fully address the pain points of millions of user groups together. We have designed a hybrid model to address the issues by using a single routing approach to view data packets. This method will prevent multiple flood attacks to a significant extent. The period base defence mechanism will be used to blacklist a source of information that has already sent the packet of data to the user and the propagation routing principle will help to find the best possible optimum path to connect the user with the information and vice versa. The flooding attack acts as a medium to denial of service, hence the root cause of the node has to be reflected properly so that future attacks can be evaluated, predicted and detected accurately with precision.