DDoS Detection Technique by Using Various Methods

There are a many network attacks on the Internet, and they are increasing each year. The condition of internet attacks is on the increase toward a distributed, collaborative direction. Internet attacks exhaust a lot of resources, take up a lot of bandwidth, making the victim host cannot accept normal network requests, resulting in substantial economic losses. In this paper explain three different methods to detect DDoS attack. This paper is based on the analysis of the distribution of network traffic, using detection method based on the analysis of the correlation of IP addresses. Next method of DDoS attacks called stealthy DDoS attacks, which can be launched by complicated attackers. Such attacks are different from traditional DDoS attacks in that they cannot be detected by previous detection methods effectively. In response to this type of DDoS attacks, in this paper a detection approach based on time-series decomposition, which divides the original time series into trend and random components. It then applies a double autocorrelation method and an superior cumulative sum technique to the trend and random components, respectively, to detect anomalies in both components.