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On the difficulty of scalably detecting network attacks
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Source Conference on Computer and Communications Security archive
Proceedings of the 11th ACM conference on Computer and communications security table of contents
Washington DC, USA
SESSION: Network intrusions table of contents
Pages: 12 - 20  
Year of Publication: 2004
ISBN:1-58113-961-6
Authors
Kirill Levchenko  University of California at San Diego
Ramamohan Paturi  University of California at San Diego
George Varghese  University of California at San Diego
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 25,   Downloads (12 Months): 136,   Citation Count: 9
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ABSTRACT

Most network intrusion tools (e.g., Bro) use per-flow state to reassemble TCP connections and fragments in order to detect network attacks (e.g., SYN Flooding or Connection Hijacking) and preliminary reconnaissance (e.g., Port Scans). On the other hand, if network intrusion detection is to be implemented at high speeds at network vantage points, some form of aggregation is necessary. While many security analysts believe that such per-flow state is required for many of these problems, there is no clear proof that this is the case. In fact, a number of problems (such as detecting large traffic footprints or counting identifiers) have scalable solutions. In this paper, we initiate the study of identifying when and how a security attack detection problem can have a scalable solution. We use tools from Communication Complexity to prove that the common formulations of many well-known intrusion detection problems (detecting SYN Flooding, Port Scans, Connection Hijacking, and content matching across fragments) require per-flow state. Our theory exposes assumptions that need to be changed to provide scalable solutions to these problems; we conclude with some systems techniques to circumvent these lower bounds.


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  9
 
 
 
 

Collaborative Colleagues:
Kirill Levchenko: colleagues
Ramamohan Paturi: colleagues
George Varghese: colleagues