An Efficient Flash Crowd Attack Detection to Internet Threat Monitors (ITM) Using Honeypots

Now a days there is a rapid increase of traffic to a given web server within a short time as the number of Internet users increases, and such a phenomenon is called a flash crowd. Once flash crowds occurs a response rate decreases or the web server may crash as the load increases. In this paper we implement the Internet Threat Monitoring (ITM), is a globally scoped Internet monitoring system whose goal is to measure, detect characterize, and track threats such as distribute denial of service (DDoS) attacks and worms. To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address flash crowd attack against ITM system in which the attacker attempt to exhaust the network and ITM’s resources, such as network bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flash crowd attacks using Botnet on ITM. Based on this model we generalize the flash crowd attacks and propose an effective attack detection using Honeypots.