NDLI: ACTM: Anomaly Connection Tree Method to detect Silent Worms

Content Provider	IEEE Xplore Digital Library
Author	Kawaguchi, N. Azuma, Y. Ueda, S. Shigeno, H. Okada, K.
Copyright Year	2006
Description	Author affiliation: Fac. of Sci. & Technol., Keio Univ., Kanagawa (Kawaguchi, N.; Azuma, Y.; Ueda, S.; Shigeno, H.; Okada, K.)
Abstract	In this paper we propose a novel worm detection method that can detect silent worms in intranet. Most existing detection methods use aggressive activities of worms as a clue for detection and are ineffective against worms that propagate silently using a list of vulnerable hosts. To detect such worms, we propose anomaly connection tree method (ACTM). ACTM uses two features present to most worms. First is that the worm's propagation behavior is expressed as tree-like structures. Second is that the worm's selection of infection targets does not consider which hosts its infected host communicates too frequently. Then, by constructing trees that are composed of anomaly connections, ACTM detects the existence of such worms. Through the simulation results, we have shown that ACTM can detect the worms in an early stage
Starting Page	901
Ending Page	908
File Size	210240
Page Count	8
File Format	PDF
ISBN	0769524664
ISSN	1550445X
DOI	10.1109/AINA.2006.70
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-04-18
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer worms Face detection Network topology Cities and towns Computational modeling Computer simulation Computer networks Network servers TCPIP Target tracking
Content Type	Text
Resource Type	Article

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