Efficient algorithms for estimating loss of information in a complex network: Applications to intentional risk analysis

Santiago Moral; Victor Chapela; Regino Criado; Ángel Pérez; Miguel Romance; Santiago Moral; Victor Chapela; Regino Criado; Ángel Pérez; Miguel Romance

doi:10.3934/nhm.2015.10.195

Networks and Heterogeneous Media

2015, Volume 10, Issue 1: 195-208. doi: 10.3934/nhm.2015.10.195

Previous Article Next Article

Efficient algorithms for estimating loss of information in a complex network: Applications to intentional risk analysis

1.
IT Risk, Fraud and Security, Research and Innovation for IT Risk, Fraud and Security, BBVA, Madrid
2.
Suggestic Inc, Palo Alto, San Francisco Bay Area, California
3.
Departamento de Matemática Aplicada, Ciencia e Ingeniería de los Materiales y Tecnología Electrónica, Universidad Rey Juan Carlos, 28933 Móstoles (Madrid)

Received: 01 July 2014 Revised: 01 December 2014
Primary: 05C90, 05C75; Secondary: 68M10, 94C15, 90B18.

In this work we propose a model for the diffusion of information in a complex network. The main assumption of the model is that the information is initially located at certain nodes and then is disseminated, with occasional losses when traversing the edges, to the rest of the network. We present two efficient algorithms, which we called max-path and sum-path, to compute, respectively, lower and upper bounds for the amount of information received at each node. Finally we provide an application of these algorithms to intentional risk analysis.
- Information diffusion,
- intentional complex network,
- intentional technological risk
Citation: Santiago Moral, Victor Chapela, Regino Criado, Ángel Pérez, Miguel Romance. Efficient algorithms for estimating loss of information in a complex network: Applications to intentional risk analysis[J]. Networks and Heterogeneous Media, 2015, 10(1): 195-208. doi: 10.3934/nhm.2015.10.195

Related Papers:

Abstract

In this work we propose a model for the diffusion of information in a complex network. The main assumption of the model is that the information is initially located at certain nodes and then is disseminated, with occasional losses when traversing the edges, to the rest of the network. We present two efficient algorithms, which we called max-path and sum-path, to compute, respectively, lower and upper bounds for the amount of information received at each node. Finally we provide an application of these algorithms to intentional risk analysis.

References

[1]	A. Barrat, M. Barthélemy and A. Vespignani, Dynamical Processes on Complex Networks, $1^{st}$ Edition, Cambridge University Press, New York, 2008. doi: 10.1017/CBO9780511791383
[2]	Y. Bar-Yam, Dynamics of Complex Systems, $1^{st}$ Edition, Addison-Wesley, Boston, 1997.
[3]	S. Boccaletti, G. Bianconi , R. Criado, C. I. del Genio, J. Gómez-Gardeñes, M. Romance, I. Sendiña-Nadal, Z. Wang and M. Zanin, The structure and dynamics of multilayer networks, Physics Reports, 544 (2014), 1-122. doi: 10.1016/j.physrep.2014.07.001
[4]	S. Boccaletti, V. Latora, Y. Moreno, M. Chavez and D.-U. Hwang, Complex networks: Structure and dynamics, Physics Reports, 424 (2006), 175-308. doi: 10.1016/j.physrep.2005.10.009
[5]	J. Borondo, F. Borondo, C. Rodriguez-Sickert and C. A. Hidalgo, To each according to its degree: The meritocracy and topocracy of embedded markets, Scientific Reports, 4 (2014), 1-7. doi: 10.1038/srep03784
[6]	V. Chapela, Tips for Managing Intentional Risk, ISACA, 2011. Available from: http://www.isaca.org/About-ISACA/-ISACA-Newsletter/.
[7]	L. R. Ford and D. R. Fulkerson, Maximal flow through a network, Canadian Journal of Mathematics, 8 (1956), 399-404. doi: 10.4153/CJM-1956-045-5
[8]	Y. Lin, J. C. S. Lui, K. Jung and S. Lim, Modelling multi-state diffusion process in complex networks: Theory and applications, 2013 International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2013, 506-513. doi: 10.1109/SITIS.2013.86
[9]	D. López-Pintado, Diffusion in complex social networks, Games and Economic Behavior, 62 (2008), 573-590. doi: 10.1016/j.geb.2007.08.001
[10]	M. E. J. Newman, The structure and function of complex networks, SIAM Review, 45 (2003), 167-256. doi: 10.1137/S003614450342480
[11]	M. Safar, K. Mahdi and S. Torabi, Network robustness and irreversibility of information diffusion in Complex networks, Journal of Computational Science, 2 (2011), 198-206. doi: 10.1016/j.jocs.2011.05.005
[12]	S. H. Strogatz, Exploring complex networks, Nature, 410 (2001), 268-276.

Reader Comments

Your name:*

Email:*
© 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)