Telecommunications & Information Technology Institute And Electrical & Computer Engineering Department C Coolllleeggee ooff E Ennggiinneeeerriinngg,, FFlloorriiddaa IInntteerrnnaattiioonnaall U Unniivveerrssiittyy Invited Talk Series Presents Modeling Internet Worm Attacks By Dr. Zesheng Chen Georgia Institute of Technology On Wednesday, May 23, 2007; 10:30AM EC 3753, 10555 West Flagler Street Abstract: As computer and communication networks become prevalent, the Internet has been a battlefield for attackers and defenders. One of the most powerful weapons for attackers is the Internet worm. Specifically, a worm attacks vulnerable computer systems and employs self-propagating methods to flood the Internet rapidly. As a result, worms, such as Code Red, Slammer, and Witty, have infected hundreds of thousands of hosts and become a significant threat to network security and management. The objective of my research is to characterize the spread of worms, analyze Internet vulnerabilities, and develop effective countermeasures. First, a discrete-time mathematical model, called the analytical active worm propagation (AAWP) model, is presented to capture the spreading dynamics of random-scanning worms. The AAWP model provides a tool for characterizing the propagation of worms using different scanning methods and for evaluating the performance of worm detection and defense systems. Second, vulnerable hosts are observed to be highly unevenly distributed in the Internet, which leads to an optimal worm scanning method called importance scanning. Such a new method is developed from and named after importance sampling in statistics and enables a worm to spread much faster than both random and routable scanning. The information of vulnerable-host distributions, however, may not be known before a worm is released. To overcome this, a self-learning worm is designed that can accurately estimate the underlying vulnerable-host distribution while propagating. Finally, a new metric, referred to as the non-uniformity factor, is presented to quantify both the unevenness of a vulnerable-host distribution and the spreading ability of network-aware worms. This metric is essentially the Renyi information entropy. Network-aware worms are shown to be able to increase the spreading speed at the early stage with a rate of nearly) the nonuniformity factor. To fight against network-aware worms, defenders should scatter applications uniformly in the entire IP-address space from the viewpoint of game theory. For more information, please contact Dr. Kia Makki at 305-348-3738