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Scalability, fidelity, and containment in the potemkin virtual honeyfarm
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Source ACM Symposium on Operating Systems Principles archive
Proceedings of the twentieth ACM symposium on Operating systems principles table of contents
Brighton, United Kingdom
SESSION: Containment table of contents
Pages: 148 - 162  
Year of Publication: 2005
ISBN:1-59593-079-5
Also published in ...
Authors
Michael Vrable  University of California, San Diego, CA
Justin Ma  University of California, San Diego, CA
Jay Chen  University of California, San Diego, CA
David Moore  University of California, San Diego, CA
Erik Vandekieft  University of California, San Diego, CA
Alex C. Snoeren  University of California, San Diego, CA
Geoffrey M. Voelker  University of California, San Diego, CA
Stefan Savage  University of California, San Diego, CA
Sponsors
ACM: Association for Computing Machinery
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 25,   Downloads (12 Months): 166,   Citation Count: 29
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ABSTRACT

The rapid evolution of large-scale worms, viruses and bot-nets have made Internet malware a pressing concern. Such infections are at the root of modern scourges including DDoS extortion, on-line identity theft, SPAM, phishing, and piracy. However, the most widely used tools for gathering intelligence on new malware -- network honeypots -- have forced investigators to choose between monitoring activity at a large scale or capturing behavior with high fidelity. In this paper, we describe an approach to minimize this tension and improve honeypot scalability by up to six orders of magnitude while still closely emulating the execution behavior of individual Internet hosts. We have built a prototype honeyfarm system, called Potemkin, that exploits virtual machines, aggressive memory sharing, and late binding of resources to achieve this goal. While still an immature implementation, Potemkin has emulated over 64,000 Internet honeypots in live test runs, using only a handful of physical servers.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  29

Collaborative Colleagues:
Michael Vrable: colleagues
Justin Ma: colleagues
Jay Chen: colleagues
David Moore: colleagues
Erik Vandekieft: colleagues
Alex C. Snoeren: colleagues
Geoffrey M. Voelker: colleagues
Stefan Savage: colleagues