Enhanced Artificial Neural Network with Particle Swarm Optimization Algorithm for Detecting Distributed Denial of Service in Cloud


  • Shashi Shekhar
  • Neeraj Varshney


The cloud computing model has become a new paradigm shift in varied application services that delivers highly callable distributed computing platforms. In spite of the fact that the cloud replica is intended to receive infinite rewards intended for every cloud partners including cloud providers (CPs), cloud customers (CCs), plus service providers (SPs), replica still has various open issues like security that effect its believability. In this job, Enhanced Artificial Neural Network with Particle Swarm Optimization (EANNPSO) is projected in order to progress the cloud execution. Information security management systems (ISMS) are characterized frameworks that give a model to setting up, actualizing, working, observing, inspecting, keeping up and improving the insurance of data resources. A attacker can make use of a cloud to give a vindictive appliance to achieve his thing which possibly a Distributed Denial of Service (DDoS) assaults in opposition to cloud itself otherwise orchestrating one more client in the cloud. . In this work, EANNPSO algorithm is projected to identify the DDoS attack efficiently using optimal objective values and hidden neuron values. The proposed EANNPSO system provides higher security performance than the existing methods.