Collaborative Verification of Forward and Reverse Reachability in the Internet Data Plane

Yang, Hongkun; Lam, Simon S.

doi:10.1109/icnp.2014.54

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…Generic Hijacking Detection. A common way to detect and assess hijacking is based on the analysis of (i) control-plane information [6,19,20,39,41,42,59], (ii) data-plane measurements [13,14,36,38,48,60], or (iii) the combination of both [5,33,35,37,52,56]. CAIR belongs to the first class.…”

Section: Related Workmentioning

confidence: 99%

CAIR: Using Formal Languages to Study Routing, Leaking, and Interception in BGP

Schlamp,

Wählisch,

Schmidt

et al. 2016

Preprint

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The Internet routing protocol BGP expresses topological reachability and policy-based decisions simultaneously in path vectors. A complete view on the Internet backbone routing is given by the collection of all valid routes, which is infeasible to obtain due to information hiding of BGP, the lack of omnipresent collection points, and data complexity. Commonly, graph-based data models are used to represent the Internet topology from a given set of BGP routing tables but fall short of explaining policy contexts. As a consequence, routing anomalies such as route leaks and interception attacks cannot be explained with graphs.In this paper, we use formal languages to represent the global routing system in a rigorous model. Our CAIR framework translates BGP announcements into a finite route language that allows for the incremental construction of minimal route automata. CAIR preserves route diversity, is highly efficient, and well-suited to monitor BGP path changes in real-time. We formally derive implementable search patterns for route leaks and interception attacks. In contrast to the state-of-the-art, we can detect these incidents. In practical experiments, we analyze public BGP data over the last seven years.

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Section: Related Workmentioning

confidence: 99%

CAIR: Using Formal Languages to Study Routing, Leaking, and Interception in BGP

Schlamp,

Wählisch,

Schmidt

et al. 2016

Preprint

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“…In this paper, we systematically tackle the important problem of how to scale the data plane verification to be applicable in real, large networks. Not only can a scalable DPV tool quickly find network errors in large networks, it can also support novel services such as fast rollback and switching among multiple data planes [21,45,67], and data plane verification across administrative domains [22,75].…”

Section: Introductionmentioning

confidence: 99%

Switch as a Verifier: Toward Scalable Data Plane Checking via Distributed, On-Device Verification

Qiao¹,

Wen²,

Huang³

et al. 2022

Preprint

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Data plane verification (DPV) is important for finding network errors. Current DPV tools employ a centralized architecture, where a server collects the data planes of all devices and verifies them. Despite substantial efforts on accelerating DPV, this centralized architecture is inherently unscalable. In this paper, to tackle the scalability challenge of DPV, we circumvent the scalability bottleneck of centralized design and design Coral, a distributed, on-device DPV framework.The key insight of Coral is that DPV can be transformed into a counting problem on a directed acyclic graph, which can be naturally decomposed into lightweight tasks executed at network devices, enabling scalability. Coral consists of (1) a declarative requirement specification language, (2) a planner that employs a novel data structure DVNet to systematically decompose global verification into on-device counting tasks, and (3) a distributed verification (DV) protocol that specifies how on-device verifiers communicate task results efficiently to collaboratively verify the requirements. We implement a prototype of Coral. Extensive experiments with real-world datasets (WAN/LAN/DC) show that Coral consistently achieves scalable DPV under various networks and DPV scenarios, i.e., up to 1250× speed up in the scenario of burst update, and up to 202× speed up on 80% quantile of incremental verification, than state-of-the-art DPV tools, with little overhead on commodity network devices.

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