• Corpus ID: 5901560

Efficient techniques for fast packet classification

@inproceedings{Tongaonkar2009EfficientTF,
  title={Efficient techniques for fast packet classification},
  author={Alok Tongaonkar},
  year={2009}
}
Stony Brook University. SBU Graduate School in Computer Science. Lawrence Martin (Dean of Graduate School), Professor R. Sekar, (Advisor) Computer Science Department, Stony Brook University, Professor I. V. Ramakrishnan, (Chairman) Computer Science Department, Stony Brook University, Professor Robert Johnson, (Committee Member) Computer Science Department, Stony Brook University, Professor Nitesh Saxena, (External Committee Member) Computer Science and Engineering Department, Polytechnic… 

Condition Factorization: A Technique for Building Fast and Compact Packet Matching Automata

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References

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A novel approach to packet classification which combines a heuristic tree search with the use of filter buckets is proposed and studied, which is unique in the sense that it can adapt to the input packet distribution by taking into account the relative filter usage.

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The packet filter is described, a kernel-resident, protocol-independent packet demultiplexer, which performs quite well, and has been in production use for several years.

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The problem of intrusion detection is restructured to allow the use of more efficient string matching algorithms that operate on sets of patterns in parallel and a new string matching algorithm is introduced that has average-case performance that is better than the best theoretical algorithm and muchbetter than the currently deployed algorithm.

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A heuristic, called HiCuts, (hierarchical intelligent cuttings), which exploits the structure found in classifiers and is found to classify packets quickly and has relatively small storage requirements.

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New packet classification schemes are presented that, with a worst-case and traffic-independent performance metric, can classify packets, by checking amongst a few thousand filtering rules, at rates of a million packets per second using range matches on more than 4 packet header fields.

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A performance study shows that the software implementation is about twice as fast as existing mechanisms, and that the hardware implementation is currently able to keep up with OC-12 network links and is likely to operate at gigabit speeds in the near future.

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This paper presents a new approach for network intrusion detection based on concise specifications that characterize normal and abnormal network packet sequences, which can easily support new network protocols as information relating to the protocols are not hard-coded into the system.