DocumentCode
1806525
Title
Hamsa: fast signature generation for zero-day polymorphic worms with provable attack resilience
Author
Li, Zhichun ; Sanghi, Manan ; Chen, Yan ; Kao, Ming-Yang ; Chavez, Brian
Author_Institution
Northwestern Univ., Evanston, IL
fYear
2006
fDate
21-24 May 2006
Lastpage
47
Abstract
Zero-day polymorphic worms pose a serious threat to the security of Internet infrastructures. Given their rapid propagation, it is crucial to detect them at edge networks and automatically generate signatures in the early stages of infection. Most existing approaches for automatic signature generation need host information and are thus not applicable for deployment on high-speed network links. In this paper, we propose Hamsa, a network-based automated signature generation system for polymorphic worms which is fast, noise-tolerant and attack-resilient. Essentially, we propose a realistic model to analyze the invariant content of polymorphic worms which allows us to make analytical attack-resilience guarantees for the signature generation algorithm. Evaluation based on a range of polymorphic worms and polymorphic engines demonstrates that Hamsa significantly outperforms Polygraph (J. Newsome et al., 2005) in terms of efficiency, accuracy, and attack resilience
Keywords
Internet; invasive software; telecommunication security; Hamsa; Internet infrastructure security; analytical attack-resilience guarantees; attack resilience; automatic signature generation; fast signature generation; high-speed network links; network-based automated signature generation system; polymorphic engines; zero-day polymorphic worms; Algorithm design and analysis; Dairy products; High-speed networks; Information security; Internet; Intrusion detection; Local area networks; Noise generators; Resilience; Telecommunication traffic;
fLanguage
English
Publisher
ieee
Conference_Titel
Security and Privacy, 2006 IEEE Symposium on
Conference_Location
Berkeley/Oakland, CA
ISSN
1081-6011
Print_ISBN
0-7695-2574-1
Type
conf
DOI
10.1109/SP.2006.18
Filename
1623999
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