Abstract
In the long term usage of the network, users will form certain types of habit according to their specific characteristics, individual hobbies and given restrictions. On the burst-out of worms, the overwhelming flow caused by random scanning will temporarily alter the behavior representation of users. Therefore, it is reasonable to conclude that the statistics and classification of the user habit can contribute to the detection of worms. On the basis of analysis about both users and worms, we construct the model of user-habit and propose a new approach for the early warning of worms. This paper possesses strong direction significance due to its broad applicability since extended models can be derived from the model proposed in this paper.
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© 2005 Springer-Verlag Berlin Heidelberg
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Wang, P., Fang, B., Yun, X. (2005). A New User-Habit Based Approach for Early Warning of Worms. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_32
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DOI: https://doi.org/10.1007/11596981_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30819-5
Online ISBN: 978-3-540-31598-8
eBook Packages: Computer ScienceComputer Science (R0)