Topological analysis of cloud service connectivity

Fabian, Benjamin; Baumann, Annika; Lackner, Jessika

doi:10.1016/j.cie.2015.06.009

Cited by 18 publications

(7 citation statements)

References 41 publications

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“…For both perspectives and most layers, there are historical examples of attacks and failures with impact on connectivity [5,8]. Some attacks on higher layers, such as BGP misconfiguration, affect the robustness of AS-level and IP-level graphs without damage to the underlying physical infrastructure and interconnections of the lower layers.…”

Section: Layer Models and Graph Models Of The Internetmentioning

confidence: 99%

“…In this equation for the Symmetry Ratio SR [118], # λ is the number of distinct eigenvalues of the adjacency matrix, and D = max m,n∈V d (m,n) the Diameter (Section 6.1). For lowsymmetry networks, SR ∈ [8,15] holds and for high-symmetry networks, SR ∈ [1,3]. In the latter case, all nodes are similarly important, and the network is more Traffic Robust against attacks as measured by the Share of Delivered Data Flow X(ζ) (Section 7.7), which then have a similar impact as failures.…”

Section: Symmetry Ratiomentioning

confidence: 99%

“…The current article uses research on Internet robustness as a guiding use case for applying graph metrics to study network robustness. However, since the application of graph theory and network science [11] (Chapter 1) is growing in many other research fields such as natural sciences [135], social networks (including networks of human actors like friends, customers, influencers, but also criminals) [136], organizational networks (such as logistics [137,138], public transportation networks [139], information and process flows) and further information technology and service networks (including application-layer communication, cloud connectivity [8], peer-to-peer systems, and blockchain transactions [140]), the present survey could also be consulted by researchers in those and further domains, whenever the robustness of networks needs to be investigated. A more detailed transfer and interpretation of metrics for further networks is left for-potentially very interesting and fruitful-future research in those fields.…”

Section: Transfer To Other Research Fieldsmentioning

confidence: 99%

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Graph Metrics for Network Robustness—A Survey

Oehlers

Fabian

2021

Mathematics

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Research on the robustness of networks, and in particular the Internet, has gained critical importance in recent decades because more and more individuals, societies and firms rely on this global network infrastructure for communication, knowledge transfer, business processes and e-commerce. In particular, modeling the structure of the Internet has inspired several novel graph metrics for assessing important topological robustness features of large complex networks. This survey provides a comparative overview of these metrics, presents their strengths and limitations for analyzing the robustness of the Internet topology, and outlines a conceptual tool set in order to facilitate their future adoption by Internet research and practice but also other areas of network science.

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Section: Layer Models and Graph Models Of The Internetmentioning

confidence: 99%

Section: Symmetry Ratiomentioning

confidence: 99%

Section: Transfer To Other Research Fieldsmentioning

confidence: 99%

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Graph Metrics for Network Robustness—A Survey

Oehlers

Fabian

2021

Mathematics

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“…Topology refers to the edge-based and structural attributes of a network or a graph (Zaki and Meira, 2014, p. 93): the various entities, such as routers, and their interconnections. The study of Internet topology enables the evaluation of performance and vulnerabilities of the Internet infrastructure and individual services in the case of failures or intentional attacks, with increasing importance in light of present cybercrime and cyber warfare (Albert and Barabási, 2000;Cohen et al 2000;Cohen et al 2001;Doyle et al, 2005;Xiao et al, 2008;Sterbenz et al 2010;Sterbenz et al 2013;Doerr and Kuipers, 2014;Baumann and Fabian, 2014;Fabian et al 2015). Internet maps are also important for the development of more effective routing algorithms and security and privacy mechanisms.…”

Section: Introductionmentioning

confidence: 99%

A multilayer graph model of the internet topology

Tilch

Ermakova

Fabian

2020

IJNVO

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Purpose: Despite intensive research during the last two decades, the detailed structural composition of the Internet is still opaque to researchers. Nevertheless, due to the importance of Internet maps for the development of more effective routing algorithms, security mechanisms, and resilience management, more detailed insights are required. This article advances the understanding of the Internet structure by integrating data from different large-scale measurement campaigns into a set of comprehensive Internet graphs at different abstraction levels, and analyzes them in terms of important statistics and graph measures. Design/methodology/approach: This study follows the topology measurement framework suggested by Gunes and Sarac (2009), involving three phases: topology collection, topology construction, and topology analysis. Findings: An integrated data set of Internet graphs at different abstraction layers is provided that can serve as a baseline for future research on Internet analytics. Furthermore, results of important graph metrics are presented and power-law relationships for the degree distributions on every level of the current Internet are substantiated. Research limitations/implications: By necessity, the integrated graphs provide a snapshot of the Internet topology. In future work, repeated measurements and automated data integration could lead to a better understanding of Internet dynamics. Practical implications: Due to increasing dependency on the Internet as a critical global infrastructure, studying Internet connectivity is more important than ever for both companies and Internet service providers. The data set will be made publically available for network research. Social implications: Understanding the structure of Internet serves as a fundamental step in improving the robustness, security, and privacy of any online service. Originality/value: By carefully integrating six different traceroute datasets such as iPlane, CAIDA, Carna, DIMES, RIPE Atlas, and RIPE IPv6L, this paper presents the Internet graphs of a substantially larger and thus solid scale than previously known, at well-established abstraction levels such as the IP interface, router, Point of Presence (PoP), Autonomous System (AS), and Internet Service Provider (ISP). Furthermore, by employing a broad diversity of graph measures, this study creates a more exhaustive snapshot of the global Internet topology than earlier works.

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“…Hence, cloud security has the influence in educational institutions. Benjamin Fabian et al discussed topological analysis of cloud service connectivity [21]. The authors focused on the network reachability of cloud services.…”

Section: Related Workmentioning

confidence: 99%

EduCloud: A Dynamic Three Stage Authentication Framework to Enhance Security in Public Cloud

Kumaresan¹,

Gopalan²

2017

IJEM

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Now-a-days, one of the most exciting technology is cloud computing. Accessing dynamically virtualized resources through internet is called as cloud computing. Security and confidentiality are the major concerns in public cloud. Though EduCloud (Educational Cloud) uses public cloud, moving data from one location to another location may lead to risk. Information related to staff, student and management or admin that can be shared in EduCloud, are to be secured in public educational cloud environment. In this scenario, data security is the most critical issue in cloud. But present authentication system available does not provide enough security in public EduCloud. Hence, we propose new authentication framework to enhance security in public educational cloud. The features of various authentication techniques are discussed in this paper and a novel framework is proposed for pubic EduCloud, which provides not only security but also improves the response time. The developed software tool is best suited and provably a secured solution to the public educational cloud environment.

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Topological analysis of cloud service connectivity

Cited by 18 publications

References 41 publications

Graph Metrics for Network Robustness—A Survey

Graph Metrics for Network Robustness—A Survey

A multilayer graph model of the internet topology

EduCloud: A Dynamic Three Stage Authentication Framework to Enhance Security in Public Cloud

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