Towards applying FCM with DBSCAN for Detecting DDoS Attack in Cloud Infrastructure to Improve Data Transmission Rate

Abstract

Cloud is a pay-to-use technology which can be used to offer IT resources instead of buying computer hardware. It is time saving and cheaper technology. This paper analyzes the DDoS attack on cloud infrastructure and can be detected by using FCM with DBSCAN hybrid algorithm that classifies the clusters of data packets and detects the outlier in that particular data packet. The experimental outcome shows that the enhanced hybrid approach has better results in detecting the DDoS attack. The DDoS attack targets the main host of the cloud infrastructure by sending unwanted packets. This attack is a major threat to the network security. The FCM with DBSCAN hybrid approach detects outliers and also assigns one specific data point in clusters to detect DDoS attack in cloud infrastructure. By using this hybrid approach the data can be grouped as clusters and the data beyond the noise level can also be detected. This algorithm helps in identifying the data that are vulnerable to DDoS attack. This detection helps in improving the data transmission rate.