A System for Denial of Service Attack Detection Based on Multivariate Correlation Analysis
Abstract In the networking systems, such as the Web servers, database servers, cloud computing servers etc are now under threads from network attackers. As one of most common and aggressive means, Denial of Service attacks cause serious impact on these computing systems. We are present a study on the recent approaches in handling Distributed Denial of Service attacks. DDOS attack is the fairly new type of attack to cripple the availability of Internet service and resources. During in the last decade, anomaly detection has attracted to the attention of many researchers to overcome the weakness of signature based is IDS in the detecting novel attacks, and KDD CUP'99 is the mostly widely used data set for the evaluation of these systems. We are survey different papers describing methods of defense against DDOS attacks based on entropy variations, traffic in anomaly parameters, neural networks, device level defense, botnet flux identification and application layer DDOS defense.