Research of internet worm warning system based on system identification

In this paper, by analyzing the worm’s propagation model, we propose a new worm warning system based on the method of system identification, and use recursive least squares algorithm to estimate the worm’s infection rate. The simulation result shows the method we adopted is an efficient way to conduct Internet worm warning.

Research of internet worm warning system

The frequent explosion of Internet worms has been one of the most serious problems in cyberspace security. In this paper, by analyzing the worm’s propagation model, we propose a new worm warning system based on the method of system identification, and use recursive least squares algorithm to estimate the worm’s infection rate. The simulation result shows the method we adopted is an efficient way to conduct Internet worm warning. Tao ZHOU received his M.S. degree in Control Theory and Control Engineering from NWPU (Northwestern Polytechnical University), 2002. Since then, he has been a Ph.D. candidate in College of Automation, NWPU. His research interests include information security, network technology and automatic control. Guanzhong DAI is a professor and supervisor of doctoral candidates in College of Automation, NWPU (Northwest Polytechnical University). His research interests include automatic control and information security. Huimin YE is a Ph.D. candidate in college of automation, NWPU (Northwest Polytechnical University). Her research interests include network security, artificial intelligence, natural language processing.