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A Difference Resolution Approach to Compressing Access Control Lists

A Difference Resolution Approach to Compressing Access Control Lists. James Daly, Alex Liu, Eric Torng Michigan State University INFOCOM 2013. Motivation. Classifiers used for many applications Packet Forwarding Firewalls Quality of Service Classifiers are growing New threats

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A Difference Resolution Approach to Compressing Access Control Lists

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  1. A Difference Resolution Approach to Compressing Access Control Lists James Daly, Alex Liu, Eric Torng Michigan State University INFOCOM 2013

  2. Motivation • Classifiers used for many applications • Packet Forwarding • Firewalls • Quality of Service • Classifiers are growing • New threats • New services

  3. Motivation • Classifier compression is an important problem • Device imposed rule limits • NetScreen-100 allows only 733 rules • Simplifies rule management • DIFANE [Yu et al. SIGCOMM 2010]

  4. Background Packet: [2, 4]

  5. Classifier Definition • Classifier : list of rules • Tupleof d intervals over finite, discrete fields • Decision (accept, deny, physical port number, etc.) • Only first matching rule applies • Classifiers equivalent if they give the same result for all inputs

  6. Problem Definition • Problem • Input: classifier • Output: smallest equivalent classifier • NP-Hard 6

  7. Prior Work • Redundancy Removal [eg. Liu and Gouda. DBSec 2005] • Iterated Strip Rule [Applegate et al. SODA 2007] • Only two dimensions • Approximation guarantee: O(min(n1/3, Opt1/2)) • Firewall Compressor [Liu et al. INFOCOM 2008] • Optimal weighted 1-D case • Works on higher dimensions

  8. Motivating Example

  9. Dimension Reduction

  10. FC: Fully Solve Each Row

  11. Diplomat: Identify and Resolve Differences

  12. Diplomat: Identify and Resolve Differences

  13. Diplomat: Identify and Resolve Differences

  14. Diplomat: Identify and Resolve Differences

  15. Higher Dimensions

  16. Diplomat • Three parts • Base solver for the last row • Firewall Compressor for 1D case • Diplomat otherwise • Resolver • Given two rows identify and resolve differences • Merge rows together into one • Scheduler • Find best order to resolve rows

  17. Different Resolvers

  18. Scheduling • Multi-row resolver: greedy schedule • Single-row resolver: dynamic programming schedule

  19. Dynamic Schedule Upper Bound Remaining Row Source Row Lower Bound

  20. Results • Comparison of Firewall Compressor and Diplomat on 40 real-life classifiers • Divided into sets based on size • Diplomat requires 30% fewer rules on largest sets • 2-D bounds: O(min(n1/3, Opt1/2)) Mean Compression Ratio

  21. Conclusion • Diplomat offers significant improvements over Firewall Compressor because it focuses on the differences between rows • Results are most pronounced on larger classifiers • Can guarantee approximation bound for 2-D classifiers

  22. Questions?

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