Visualizing Internet Routing Changes

Lad, Mohit; Massey, Daniel; Zhang, L.

doi:10.1109/tvcg.2006.108

Cited by 34 publications

(26 citation statements)

References 18 publications

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“…Counting paths in order to identify (or narrow down) a root cause for a routing change has been explored before, e.g. [16]. However, PathMiner differs from such previous work in terms of goals (since it particularly focuses on large events that may re-occur over time) and in methods (since it carefully chooses the set of paths to analyze).…”

Section: Algorithmmentioning

confidence: 99%

“…In [17,16] the authors propose a way to identify temporal event boundaries in the stream of update messages and a visualization tool that allows users to narrow down and infer root causes. Our work, on the other hand, does not rely on inferring the state of the routing system by using update messages (in fact this is a hard task, since in most cases internal AS policies are unknown).…”

Section: Related Workmentioning

confidence: 99%

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Identifying and Analyzing High Impact Routing Events with PathMiner

Comarela

Crovella

2014

Proceedings of the 2014 Conference on Internet Measurement Conference

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Understanding the dynamics of the interdomain routing system is challenging. One reason is that a single routing or policy change can have far reaching and complex effects. Connecting observed behavior with its underlying causes is made even more difficult by the amount of noise in the BGP system. In this paper we address these challenges by presenting PathMiner, a system to extract large scale routing events from background noise and identify the AS or link responsible for the event.PathMiner is distinguished from previous work in its ability to identify and analyze large-scale events that may re-occur many times over long timescales. The central idea behind PathMiner is that although a routing change at one AS may induce large-scale, complex responses in other ASes, the correlation among those responses (in space and time) helps to isolate the relevant set of responses from background noise, and makes the cause much easier to identify. Hence, PathMiner has two components: an algorithm for mining large scale coordinated changes from routing tables, and an algorithm for identifying the network element (AS or link) responsible for the set of coordinated changes.We describe the implementation and validation of PathMiner. We show that it is scalable, being able to extract significant events from multiple years of routing data at a daily granularity. Finally, using PathMiner we study interdomain routing over past 9 years and use it to characterize the presence of large scale routing events and to identify the responsible network elements.

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Section: Algorithmmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Identifying and Analyzing High Impact Routing Events with PathMiner

Comarela

Crovella

2014

Proceedings of the 2014 Conference on Internet Measurement Conference

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“…BGPlay [6], [7], [8], BGPviz 2 , Link-Rank [9], VAST [11], TAMP [10] and Event Shrub [12] focus on a high-level AS view, while ELISHA [13] and PGPeep [14] provide low-level IP views. Some other tools, like BGP Eye [15] and RIPEstat 3 have multiple views to address specific aspects of the data.…”

Section: Visualization Of Bgp Datamentioning

confidence: 99%

Visual analytics for BGP monitoring and prefix hijacking identification

et al. 2012

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Abstract-The control plane of the Internet relies entirely on BGP as inter-domain routing protocol to maintain and exchange routing information between large network providers and their customers. However, an intrinsic vulnerability of the protocol is its inability to validate the integrity and correctness of routing information exchanged between peer routers. As a result, it is relatively easy for people with malicious intent to steal legitimate IP blocks through an attack known as prefix hijacking, which essentially consists in injecting bogus routing information into the system to redirect or subvert network traffic. In this paper, we give a short survey of visualization methods that have been developed for BGP monitoring, in particular for the identification of prefix hijacks. Our goal is to illustrate how network visualization has the potential to assist an analyst in detecting abnormal routing patterns in massive amounts of BGP data. Finally, we present an analysis of a real validated case of prefix hijacking, which took place between April and August 2011. We use this hijack case study to illustrate the ongoing work carried out in VIS-SENSE, a European research project that leverages visual analytics to develop more effective tools for BGP monitoring and prefix hijack detection.

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“…They witnessed 19,000 ASs and 60,000 links. Likewise, Lad et al counted more than 20,000 ASs in 2006 [6]. Wang et al [7] studied the consequences of having inflated paths on ASs' inbound traffic.…”

Section: Introductionmentioning

confidence: 99%

On the characteristics of BGP routes

Clément

Chin

2007

2007 International Symposium on Communications and Information Technologies

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This paper studies the characteristics of Border Gateway Protocol (BGP) routes. In particular, it identifies autonomous systems (ASs) that appear frequently in path vectors. In addition, it analyzes path vector lengths. Finally, it investigates the prevalence of inflated paths, commonly used by ASs for traffic engineering purposes. Disciplines Physical Sciences and Mathematics Publication DetailsThis conference paper was originally published as Clement, J, Chin, K, On Abstract-This paper studies the characteristics of Border Gateway Protocol (BGP) routes. In particular, it identifies autonomous systems (ASs) that appear frequently in path vectors. In addition, it analyzes path vector lengths. Finally, it investigates the prevalence of inflated paths, commonly used by ASs for traffic engineering purposes.

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Visualizing Internet Routing Changes

Cited by 34 publications

References 18 publications

Identifying and Analyzing High Impact Routing Events with PathMiner

Identifying and Analyzing High Impact Routing Events with PathMiner

Visual analytics for BGP monitoring and prefix hijacking identification

On the characteristics of BGP routes

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