After many Internet-scale worm incidents in recent years, it is clear that a simple self-propagation worm can quickly spread across the Internet. And every worm incidents can cause severe damage to our society. So it is necessary to build a system that can detect the presence of worm as quickly as possible. This paper first analyzes the worm's framework and its propagation model. Then, we describe a new algorithm for detecting worms. Our algorithm first monitors the computers on network and gets the number of abnormal computers. Then based on the monitoring result, we detect an unknown worm by using recursive least squares estimation. The experiments result proves that our approach is effective to detect unknown worm. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Bo, C., Fang, B. X., & Yun, X. C. (2006). Adaptive method for monitoring network and early detection of Internet worms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3975 LNCS, pp. 178–189). Springer Verlag. https://doi.org/10.1007/11760146_16
Mendeley helps you to discover research relevant for your work.