DocumentCode
1736786
Title
W-Aegis: A Propagation Behavior Based Worm Detection Model for Local Networks
Author
Tang, Zhanyong ; Qi, Rui ; Fang, Dingyi ; Luo, YangXia
Author_Institution
Coll. of Inf. Sci. & Technol., Northwest Univ., Xi´´an, China
Volume
2
fYear
2009
Firstpage
158
Lastpage
162
Abstract
This paper presents a new approach to detect unknown worms on local networks. We propose a worm detection model based on propagation behavior of unknown worms within an intranet. The model firstly describes propagation behavior with a binary model vector structure. Then, it uses three-tier security filters to detect unknown worms. In contrast to traditional research which only focuses on how to detect the scanning behavior, the binary model vector also concerns the response behavior of the worm host. Comparison results show that it can remarkably improve the integrality of description of unknown wormspsila propagation behavior. Experimental results indicate that it is more accurately and efficiently in detecting local-network-worm-intrusion than traditional schemes.
Keywords
intranets; invasive software; telecommunication security; Intranet; W-aegis; binary model vector structure; local network worm intrusion; security filter; unknown worm detection model; Data mining; Educational institutions; Face detection; Filters; Finance; Frequency; IP networks; Information science; Information security; Paper technology; detection; local network; propagation behavior; worm;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location
Xian
Print_ISBN
978-0-7695-3744-3
Type
conf
DOI
10.1109/IAS.2009.293
Filename
5283125
Link To Document