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Context-aware clustering of DNS query traffic
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Internet Measurement Conference archive
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement table of contents
Vouliagmeni, Greece
SESSION: Infrastructure table of contents
Pages 217-230  
Year of Publication: 2008
ISBN:978-1-60558-334-1
Authors
David Plonka  University of Wisconsin - Madison, Madison, WI, USA
Paul Barford  University of Wisconsin - Madison and Nemean Networks, Madison, WI, USA
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The Domain Name System (DNS) is a one of the most widely used services in the Internet. In this paper, we consider the question of how DNS traffic monitoring can provide an important and useful perspective on network traffic in an enterprise. We approach this problem by considering three classes of DNS traffic: canonical (i.e., RFC-intended behaviors), overloaded (e.g.,black-list services), and unwanted (i.e., queries that will never succeed). We describe a context-aware clustering methodology that is applied to DNS query-responses to generate the desired aggregates. Our method enables the analysis to be scaled to expose the desired level of detail of each traffic type, and to expose their time varying characteristics. We implement our method in a tool we call TreeTop, which can be used to analyze and visualize DNS traffic in real-time. We demonstrate the capabilities of our methodology and the utility of TreeTop using a set of DNS traces that we collected from our campus network over a period of three months. Our evaluation highlights both the coarse and fine level of detail that can be revealed by our method. Finally, we show preliminary results on how DNS analysis can be coupled with general network traffic monitoring to provide a useful perspective for network management and operations.


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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Collaborative Colleagues:
David Plonka: colleagues
Paul Barford: colleagues