Enhanced CBF Packet Filtering Method to Detect DDoS Attack in Cloud Computing Environment

TL;DR

This paper proposes an enhanced confidence-based filtering method tailored for cloud environments to effectively detect and mitigate DDoS attacks, aiming to improve processing speed and reduce bandwidth usage.

Contribution

It introduces a modified CBF approach utilizing correlation patterns to better defend against DDoS attacks in cloud computing environments.

Findings

Improved detection accuracy of DDoS attacks.

Reduced bandwidth consumption during attack mitigation.

Faster processing speed for victim servers.

Abstract

Tremendous and extraordinary growths in the field of internet, intranet, extranet and its users have developed an innovative era of great global competition and contention. Denial of service attack by multiple nodes is accomplished of disturbing the services of rival servers. The attack can be for multiple reasons. So it is a major threat for cloud environment. Due to low effectiveness and large storage conventional defending approaches cannot be easily applied in cloud security. The effects of various attacks can decrease the influence of a cloud. So, in view of this challenge task, this paper aims at enhancing a proposed method for cloud security. We propose a modification to the confidence Based Filtering method (CBF) which is investigated for cloud computing environment based on correlation pattern to mitigate DDoS attacks on Cloud. The modification introduces nominal additional bandwidth and tries to increase the processing speed of the victim initiated server.