TY  - GEN
A1  - Fabian, Benjamin
A1  - Baumann, Annika
A1  - Ehlert, Mathias
A1  - Ververis, Vasilis
A1  - Ermakova, Tatiana
T1  - CORIA - Analyzing internet connectivity risks using network graphs
T2  - 2017 IEEE International Conference on Communications (ICC)
N2  - The Internet can be considered as the most important infrastructure for modern society and businesses. A loss of Internet connectivity has strong negative financial impacts for businesses and economies. Therefore, assessing Internet connectivity, in particular beyond their own premises and area of direct control, is of growing importance in the face of potential failures, accidents, and malicious attacks. This paper presents CORIA, a software framework for an easy analysis of connectivity risks based on large network graphs. It provides researchers, risk analysts, network managers and security consultants with a tool to assess an organization's connectivity and paths options through the Internet backbone, including a user-friendly and insightful visual representation of results. CORIA is flexibly extensible in terms of novel data sets, graph metrics, and risk scores that enable further use cases. The performance of CORIA is evaluated by several experiments on the Internet graph and further randomly generated networks.
KW  - risk analysis
KW  - connectivity
KW  - graph analysis
KW  - complex networks
KW  - Internet
Y1  - 2017
SN  - 978-1-4673-8999-0
SN  - 978-1-4673-9000-2
U6  - https://doi.org/10.1109/ICC.2017.7996828
SN  - 1550-3607
PB  - IEEE
CY  - Piscataway
ER  - 
TY  - JOUR
A1  - Dombrowski, Sebastian
A1  - Ermakova, Tatiana
A1  - Fabian, Benjamin
T1  - Graph-based analysis of cloud connectivity at the internet protocol level
JF  - International Journal of Communication Networks and Distributed Systems (IJCNDS)
N2  - Internet connectivity of cloud services is of exceptional importance for both their providers and consumers. This article demonstrates the outlines of a method for measuring cloud-service connectivity at the internet protocol level from a client's perspective. For this, we actively collect connectivity data via traceroute measurements from PlanetLab to several major cloud services. Furthermore, we construct graph models from the collected data, and analyse the connectivity of the services based on important graph-based measures. Then, random and targeted node removal attacks are simulated, and the corresponding vulnerability of cloud services is evaluated. Our results indicate that cloud service hosts are, on average, much better connected than average hosts. However, when interconnecting nodes are removed in a targeted manner, cloud connectivity is dramatically reduced.
KW  - cloud computing
KW  - connectivity
KW  - availability
KW  - reliability
KW  - internet topology
KW  - graph analysis
KW  - complex networks
Y1  - 2019
U6  - https://doi.org/10.1504/IJCNDS.2019.100644
SN  - 1754-3916
SN  - 1754-3924
VL  - 23
IS  - 1
SP  - 117
EP  - 142
PB  - Inderscience Enterprises Ltd
CY  - Geneva
ER  -