Secure network provenance

  • Authors:
  • Wenchao Zhou;Qiong Fei;Arjun Narayan;Andreas Haeberlen;Boon Thau Loo;Micah Sherr

  • Affiliations:
  • University of Pennsylvania;University of Pennsylvania;University of Pennsylvania;University of Pennsylvania;University of Pennsylvania;Georgetown University

  • Venue:
  • SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles
  • Year:
  • 2011

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Abstract

This paper introduces secure network provenance (SNP), a novel technique that enables networked systems to explain to their operators why they are in a certain state -- e.g., why a suspicious routing table entry is present on a certain router, or where a given cache entry originated. SNP provides network forensics capabilities by permitting operators to track down faulty or misbehaving nodes, and to assess the damage such nodes may have caused to the rest of the system. SNP is designed for adversarial settings and is robust to manipulation; its tamper-evident properties ensure that operators can detect when compromised nodes lie or falsely implicate correct nodes. We also present the design of SNooPy, a general-purpose SNP system. To demonstrate that SNooPy is practical, we apply it to three example applications: the Quagga BGP daemon, a declarative implementation of Chord, and Hadoop MapReduce. Our results indicate that SNooPy can efficiently explain state in an adversarial setting, that it can be applied with minimal effort, and that its costs are low enough to be practical.