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Cited by 1,405

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2014 IEEE Global Communications Conference

·2014

Abstract

A route leak can be defined as a security gap that occurs due to the infringement of the routing policies that any two Autonomous Systems (ASes) have agreed upon. Route leaks are seemingly simple, but hard to resolve since the ASes keep their routing policies confidential. Indeed, the traditional palliatives, such as the utilization of route filters, are no longer used by a large number of ASes, given the high administrative burden that they entail. Other alternatives, like BGP monitoring tools, not only require third party information gathered at multiple vantage points, but also they become impotent in many cases, due to their limited view of the interdomain routing state. In this paper, we propose a different approach, which allows to autonomously detect the occurrence of route leaks by solely inspecting the BGP information available at the AS. Our main contributions can be summarized as follows. First, we propose a self-contained Route Leak Detection (RLD) technique, which is based on real-time analytics on the Route Information Bases (RIBs) of the border routers of an AS. Second, we introduce Benign Fool Back (BFB), "a harmless bluff" that can substantially improve the success rate of the RLD technique. Third, we show through exhaustive simulations that our technique can detect route leak incidents in various scenarios with high success rate. In addition, our solution has the following practical advantages: a) no reliance on third party information (e.g., on vantage points); b) no changes required to control-plane protocols (e.g., to BGP); and c) allows non-invasive integration (e.g., using SDN).

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Metadata

Publisher
IEEE
Published
2014
OpenAlex
W4234865505
Cited by
1,405
References
0
Type
paratext
Language
en
Open access
closed

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CoChat. (2026). Citation check: 2014 IEEE Global Communications Conference. https://app.cochat.ai/papers/10.1109/globecom18177.2014
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2014 IEEE Global Communications Conference. (2014). https://doi.org/10.1109/globecom18177.2014

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.