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BGP Beacons, Network Tomography, and Bayesian Computation to Locate Route Flap Damping

Published:27 October 2020Publication History

ABSTRACT

Pinpointing autonomous systems which deploy specific inter-domain techniques such as Route Flap Damping (RFD) or Route Origin Validation (ROV) remains a challenge today. Previous approaches to detect per-AS behavior often relied on heuristics derived from passive and active measurements. Those heuristics, however, often lacked accuracy or imposed tight restrictions on the measurement methods.

We introduce an algorithmic framework for network tomography, BeCAUSe, which implements Bayesian Computation for Autonomous Systems. Using our original combination of active probing and stochastic simulation, we present the first study to expose the deployment of RFD. In contrast to the expectation of the Internet community, we find that at least 9% of measured ASs enable RFD, most using deprecated vendor default configuration parameters. To illustrate the power of computational Bayesian methods we compare BeCAUSe with three RFD heuristics. Thereafter we successfully apply a generalization of the Bayesian method to a second challenge, measuring deployment of ROV.

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References

  1. Ruwaifa Anwar, Haseeb Niaz, David Choffnes, Ítalo Cunha, Phillipa Gill, and Ethan Katz-Bassett. 2015. Investigating Interdomain Routing Policies in the Wild. In Proc. of ACM IMC. ACM, New York, NY, USA, 71--77.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. P. Barford, N. Duffield, A. Ron, and J. Sommers. 2009. Network Performance Anomaly Detection and Localization. In Prof. of IEEE INFOCOM. IEEE Press, Piscataway, NJ, USA, 1377--1385.Google ScholarGoogle Scholar
  3. A. Batsakis, T. Malik, and A. Terzis. 2005. Practical Passive Lossy Link Inference. In Proc. of PAM (LNCS, Vol. 3431). Springer-Verlag, Berlin, Heidelberg, 362--367.Google ScholarGoogle Scholar
  4. Steve Brooks, Andrew Gelman, Galin Jones, and Xiao-Li Meng (Eds.). 2011. Handbook of Markov Chain Monte Carlo. CRC Press, Boca Raton, FL, USA.Google ScholarGoogle Scholar
  5. Randy Bush, Cristel Pelsser, Mirjam Kuhne, Olaf Maennel, Pradosh Mohapatra, Keyur Patel, and Rob Evans. 2013. RIPE Routing Working Group Recommendations on Route Flap Damping. RIPE Document ripe-580. RIPE.Google ScholarGoogle Scholar
  6. R. Cáceres, N.G. Duffield, J. Horowitz, and D. Towsley. 1999. Multicast-based inference of network-internal loss characteristics. IEEE Trans. in Information Theory 45, 7 (1999), 2462--2480.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Matthew Caesar, Lakshminarayanan Subramanian, and Randy H. Katz. 2003. Towards Localizing Root Causes of BGP Dynamics. Technical Report UCB/CSD-03-1292. EECS Department, University of California, Berkeley. http://www2.eecs.berkeley.edu/Pubs/TechRpts/2003/6364.htmlGoogle ScholarGoogle Scholar
  8. Rui Castro, Mark Coates, Gang Liang, Robert Nowak, and Bin Yu. 2004. Network Tomography: Recent Developments. Statist. Sci. 19, 3 (2004), 499--517.Google ScholarGoogle ScholarCross RefCross Ref
  9. Di-Fa Chang, Ramesh Govindan, and John Heidemann. 2004. Locating BGP Missing Routes Using Multiple Perspectives. In Proc. of the ACM SIGCOMM Workshop on Network Troubleshooting: Research, Theory and Operations Practice Meet Malfunctioning Reality (NetT). ACM, New York, NY, USA, 301--306.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Shinyoung Cho, Rishab Nithyanand, Abbas Razaghpanah, and Phillipa Gill. 2017. A Churn for the Better: Localizing Censorship using Network-level Path Churn and Network Tomography. In Proc. of ACM CoNext. ACM, New York, NY, USA, 81--87.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Cloudflare. 2020. Is BGP safe yet? https://isbgpsafeyet.com/.Google ScholarGoogle Scholar
  12. M. Coates and R. Nowak. 2000. Network loss inference using unicast end-to-end measurements. In Proc. of ITC Specialist Seminar on IP Traffic Measurement, Modeling and Managemen. Monterey, CA, 28-1-28-9. Preprint https://hdl.handle.net/1911/19810.Google ScholarGoogle Scholar
  13. Simon Duane, A.D. Kennedy, Brian J. Pendleton, and Duncan Roweth. 1987. Hybrid Monte Carlo. Physics Letters B 195, 2 (1987), 216 - 222.Google ScholarGoogle ScholarCross RefCross Ref
  14. N. Duffield. 2006. Network Tomography of Binary Network Performance Characteristics. IEEE Transactions on Information Theory 52, 12 (2006), 5373--5388.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. N.G. Duffield, J. Horowitz, F. Lo Presti, and D. Towsley. 2002. Multicast topology inference from measured end-to-end loss. IEEE Transactions in Information Theory 48, 1 (2002), 26--45.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. N.G. Duffield, F. Lo Presti, V. Paxson, and D. Towsley. 2001. Inferring link loss using striped unicast probes. In Proc. of IEEE Infocom. IEEE Press, Piscataway, NJ, USA, 22--26.Google ScholarGoogle Scholar
  17. J. Durand, I. Pepelnjak, and G. Doering. 2015. BGP Operations and Security. RFC 7454. IETF.Google ScholarGoogle Scholar
  18. Anja Feldmann, Olaf Maennel, Z. Morley Mao, Arthur Berger, and Bruce Maggs. 2004. Locating Internet Routing Instabilities. In Proc. of ACM SIGCOMM. ACM, New York, NY, USA, 205--218.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Romain Fontugne, Esteban Bautista, Colin Petrie, Yutaro Nomura, Patrice Abry, Paulo Gonçalves, Kensuke Fukuda, and Emile Aben. 2019. BGP Zombies: An Analysis of Beacons Stuck Routes. In Proc. of PAM Conf. (LNCS, Vol. 11419). Springer, Berlin Heidelberg, 197--209.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. D. Ghita, H. Nguyen, M. Kurant, K. Argyraki, and P. Thiran. 2010. Netscope: Practical Network Loss Tomography. In Proc. of IEEE INFOCOM. IEEE Press, Piscataway, NJ, USA, 1--9.Google ScholarGoogle Scholar
  21. Yossi Gilad, Avichai Cohen, Amir Herzberg, Michael Schapira, and Haya Shulman. 2017. Are We There Yet? On RPKI's Deployment and Security. In Proc. of NDSS. ISOC, Reston, USA, 15.Google ScholarGoogle ScholarCross RefCross Ref
  22. W. K. Hastings. 1970. Monte Carlo Sampling Methods Using Markov Chains and Their Applications. Biometrika 57, 1 (1970), 97--109.Google ScholarGoogle ScholarCross RefCross Ref
  23. IIT-CNR. 2020. Isolario Project. https://www.isolario.it/.Google ScholarGoogle Scholar
  24. Zhuoqing Morley Mao, Ramesh Govindan, George Varghese, and Randy H. Katz. 2002. Route Flap Damping Exacerbates Internet Routing Convergence. In Proc. of ACM SIGCOMM. ACM, New York, NY, USA, 221--233.Google ScholarGoogle Scholar
  25. Nicholas Metropolis and S. Ulam. 1949. The Monte Carlo Method. J. Amer. Statist. Assoc. 44, 247 (1949), 335--341. http://www.jstor.org/stable/2280232Google ScholarGoogle ScholarCross RefCross Ref
  26. P. Mohapatra, J. Scudder, D. Ward, R. Bush, and R. Austein. 2013. BGP Prefix Origin Validation. RFC 6811. IETF.Google ScholarGoogle Scholar
  27. W. Mühlbauer, A. Feldmann, O. Maennel, M. Roughan, and S. Uhlig. 2006. Building an AS-topology model that captures route diversity. In Proc. of ACM SIGCOMM. ACM, New York, NY, USA, 195--206.Google ScholarGoogle Scholar
  28. H.X. Nguyen and P. Thiran. 2007. The Boolean Solution to the Congested IP Link Location Problem: Theory and Practice. In Proc. of IEEE INFOCOM. IEEE Press, Piscataway, NJ, USA, 2117--2125.Google ScholarGoogle Scholar
  29. Venkata N. Padmanabhan, Lili Qiu, and Helen J. Wang. 2002. Passive network tomography using Bayesian inference. In Proc. of ACM Internet Measurement Workshop. ACM, New York, NY, USA, 93--94.Google ScholarGoogle Scholar
  30. Cristel Pelsser, Olaf Maennel, Pradosh Mohapatra, Randy Bush, and Keyur Patel. 2011. Route Flap Damping Made Usable. In Proc. of PAM Conf. (LNCS, Vol. 6579). Springer, Berlin Heidelberg, 143--152.Google ScholarGoogle ScholarCross RefCross Ref
  31. Y. Rekhter, T. Li, and S. Hares. 2006. A Border Gateway Protocol 4 (BGP-4). RFC 4271. IETF.Google ScholarGoogle Scholar
  32. Andreas Reuter, Randy Bush, Italo Cunha, Ethan Katz-Bassett, Thomas C. Schmidt, and Matthias Wählisch. 2018. Towards a Rigorous Methodology for Measuring Adoption of RPKI Route Validation and Filtering. ACM Sigcomm Computer Communication Review 48, 1 (January 2018), 19--27.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. RIPE 2020. Routing Information Service (RIS). http://www.ripe.net/projects/ris/rawdata.htmlGoogle ScholarGoogle Scholar
  34. RIPE NCC. 2020. Current RIS Routing Beacons. https://www.ripe.net/analyse/internet-measurements/routing-information-service-ris/current-ris-routing-beacons.Google ScholarGoogle Scholar
  35. Christian P. Robert and George Casella. 2005. Monte Carlo Statistical Methods (Springer Texts in Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA.Google ScholarGoogle Scholar
  36. Matthew Roughan, Walter Willinger, Olaf Maennel, Debbie Perouli, and Randy Bush. 2011. 10 Lessons from 10 Years of Measuring and Modeling the Internet's Autonomous Systems. IEEE Journal on Selected Areas in Communications 29, 9 (2011), 1810--1821.Google ScholarGoogle ScholarCross RefCross Ref
  37. Brandon Schlinker, Todd Arnold, Italo Cunha, and Ethan Katz-Bassett. 2019. PEERING: Virtualizing BGP at the Edge for Research. In Proc. of ACM CoNEXT. ACM, New York, NY, USA, 51--67.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Philip Smith and Christian Panigl. 2006. RIPE Routing-WG Recommendation For Coordinated Route-flap Damping Parameters. RIPE Document ripe-378. RIPE.Google ScholarGoogle Scholar
  39. Joel Sommers, Paul Barford, Nick Duffield, and Amos Ron. 2007. Accurate and Efficient SLA Compliance Monitoring. In Proc. of ACM SIGCOMM (Kyoto, Japan). Association for Computing Machinery, New York, NY, USA, 109--120. https://doi.org/10.1145/1282380.1282394Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Florian Streibelt, Franziska Lichtblau, Robert Beverly, Anja Feldmann, Cristel Pelsser, Georgios Smaragdakis, and Randy Bush. 2018. BGP Communities: Even More Worms in the Routing Can. In Proceedings of the Internet Measurement Conference 2018. ACM, New York, NY, USA, 279--292.Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Cecilia Testart, Philipp Richter, Alistair King, Alberto Dainotti, and David Clark. 2020. To Filter or Not to Filter: Measuring the Benefits of Registering in the RPKI Today. In Proc. of PAM Conf. (LNCS, Vol. 12048). Springer, Berlin Heidelberg, 71--87.Google ScholarGoogle ScholarCross RefCross Ref
  42. University of Oregon. 2017. Route Views Project. http://www.routeviews.org/.Google ScholarGoogle Scholar
  43. C. Villamizar, R. Chandra, and R. Govindan. 1998. BGP Route Flap Damping. RFC 2439. IETF.Google ScholarGoogle Scholar

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  1. BGP Beacons, Network Tomography, and Bayesian Computation to Locate Route Flap Damping

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        • Published in

          cover image ACM Conferences
          IMC '20: Proceedings of the ACM Internet Measurement Conference
          October 2020
          751 pages
          ISBN:9781450381383
          DOI:10.1145/3419394

          Copyright © 2020 ACM

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          • Published: 27 October 2020

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