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

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

Estimation of communication-delays through adaptive synchronization of chaos

This paper deals with adaptive synchronization of chaos in the presence of time-varying communication-delays. We consider two bidirectionally coupled systems that seek to synchronize through a signal that each system sends to the other one and is transmitted with an unknown time-varying delay. We show that an appropriate adaptive strategy can be devised that is successful in dynamically identifying the time-varying delay and in synchronizing the two systems. The performance of our strategy with respect to the choice of the initial conditions and the presence of noise in the communication channels is tested by using numerical simulations. Another advantage of our approach is that in addition to estimating the communication-delay, the adaptive strategy could be used to simultaneously identify other parameters, such as e.g., the unknown time-varying amplitude of the received signal.Comment: Accepted for publication in Chaos, Solitons & Fractal