Mitigation of DDoS threat to service attainability in cloud premises

Abstract

Cloud environment provides users with amicable services that help them to attain their organisational and personal goals. The end user suffers from unavailability and delay of promised services under few circumstances. This is due to distributed denial of service (DDoS) attack where the illegitimate users on cloud who always generate different kinds of bots and zombies to disrupt or breakdown service availability. A DDoS detection algorithm (DDA) is proposed to trace out the existing attack by employing action-based monitoring (AM) approach on the incoming traffic. The human discovery algorithm (HDA) is implemented by performing a Turing test targeting on human to segregate the bots from the normal user. The supervisor self-learning algorithm (SSLA) is another mitigation test that allows future bots to be isolated. This model has shown improvement in terms of client success ratio, load balancing, and detection, prevention and mitigation of DDoS attack with respect to time.