Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
726352 | The Journal of China Universities of Posts and Telecommunications | 2007 | 6 Pages |
Abstract
In recent years, fast spreading worm has become one of the major threats to the security of the Internet and has an increasingly fierce tendency. In view of the insufficiency that based on Kalman filter worm detection algorithm is sensitive to interval, this article presents a new data collection plan and an improved worm early detection method which has some deferent intervals according to the epidemic worm propagation model, then proposes a worm response mechanism for slowing the wide and fast worm propagation effectively. Simulation results show that our methods are able to detect worms accurately and early.
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