TOWER: Topology Optimization for netWork Enhanced Resilience
Enrique de la Hoz, Jose Manuel Gimenez-Guzman, German Lopez-Civera, Ivan Marsa-Maestre, David Orden
2016
Abstract
Nowadays society is more and more dependent on critical infrastructures. Critical network infrastructures (CNI) are communication networks whose disruption can create a severe impact on other systems including critical infrastructures. In this work, we propose TOWER, a framework for the provision of adequate strategies to optimize service provision and system resilience in CNIs. The goal of TOWER is being able to compute new network topologies for CNIs under the event of malicious attacks. For doing this, TOWER takes into account a risk analysis of the CNI, the results from a cyber-physical IDS and a multilayer model of the network, for taking into account all the existing dependences. TOWER analyses the network structure in order to determine the best strategy for obtaining a network topology, taking into account the existing dependences and the potential conflicting interests when not all requirements can be met. Finally, we present some lines for further development of TOWER.
References
- Albert, R. Error and attack tolerance of complex networks. Nature, 406(6794), 378-382.
- Berezin, Y. “Localized attacks on spatially embedded networks with dependencies,” Scientific reports 5.
- Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. and Hwang, D. U. Complex networks: Structure and dynamics. Physics reports, 424(4), 175-308. (2006).
- Brin, S. and Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks and ISDN Systems 30, 107-117 (1998).
- Carley, K.M. "Toward an interoperable dynamic network analysis toolkit." Decis. Support Syst., 43, 1324-1347. (2007).
- Chakrabarti, S., Dom, B., Kumar, R., Raghavan, P., Rajagopalan, S., Tomkins, A., Gibson, and D., Kleinberg, J.: Mining the web's link structure. IEEE Computer 32, 60-67 (1999).
- Chechetka, A. and K. Sycara, No-commitment branch and bound search for distributed constraint optimization. AAMAS International Conference. Hakodate, Japan. (2006).
- Chierichetti, F., Epasto, A., Kumar, R., Lattanzi, and S., Mirrokni, V.: Efficient algorithms for public-private social networks. In: Proceedings of the 21st ACMSIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15). pp. 139-148 (2015).
- Davin, J. and Modi, P.J. Impact of problem centralization in distributed constraint optimization algorithms. AAMAS International Conference. (2005).
- DHS, A Roadmap for Cybersecurity Research, Technical Report, Department of Homeland Security (DHS). (2009).
- Davin, K. Impact of problem centralization in distributed constraint optimization algorithms. In Proceedings of The 4th International Conference on Autonomous Agents and Multiagent Systems AAMAS. (2005).
- Dietzel, S. A resilient in-network aggregation mechanism for VANETs based on dissemination redundancy, Ad Hoc Networks 37, 101-109. (2016).
- Fan, R. RobustGeo: A Disruption-Tolerant Geo-Routing Protocol, 24th International Conference on Computer Communication and Networks (ICCCN). (2015).
- Freeman, L.: Centrality in social networks: Conceptual clarification. Social Networks 1, 215-239 (1979).
- Goldberg, S. Why is it taking so long to secure internet routing? Communications of the ACM, 57(10), 56-63. (2014).
- Katz, L. A New Status Index Derived from Sociometric Index. Psychometrika, 39-43. (1953).
- Kimura, M., Saito, K., Ohara, K., and Motoda, H.: Speeding-up node influence computation for huge social networks. International Journal of Data Science and Analytics 1, 1-14 (2016).
- Kivelä, M. Multilayer networks, Journal of Complex Networks, 2(3), 203-271. (2014).
- Klein, M., P. Faratin, H. Sayama and Y. Bar-Yam. Negotiating Complex Contracts. Group Decision and Negotiation 12(2), 111 - 125. (2003).
- Koschützki, D., Lehmann, K.A, Peeters, L., Richter, S. Tenfelde-Podehl, D. and Zlotowski, O.. Centrality indices. Network analysis. Lecture Notes in Computer Science. 3418:16-61, (2005).
- Landmark, L. Resilient internetwork routing over heterogeneous mobile military networks, IEEE Military Communications Conference (MILCOM), 388-394. (2015).
- Li, M., Q. B. Vo and R. Kowalczyk Searching for fair joint gains in agent-based negotiation. Autonomous Agents and Multi-agent Systems (AAMAS-09). (2009).
- Lin, H. S. and Goodman S. E. Toward a Safer and More Secure Cyberspace, National Academies Press (2007).
- Marsa-Maestre, I., Lopez-Carmona, M. A., Velasco, J. R., and de la Hoz, E. Effective bidding and deal identification for negotiations in highly nonlinear scenarios. In Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems 2, 1057-1064. (2009).
- Myerson, Roger B. Game theory. Harvard university press, (2013).
- Newman, M. Networks: an introduction. Oxford University Press, (2010).
- Ohara, K., Saito, K., Kimura, and M., Motoda, H.: Resampling-based framework for estimating node centrality of large social network. In: Proceedings of the 17th International Conference on Discovery Science (DS'14). pp. 228-239. LNAI 8777 (2014).
- Pham, L., Teich, J., Wallenius, H., and Wallenius, J. Multi-attribute online reverse auctions: Recent research trends. European Journal of Operational Research, 242(1), 1-9. (2015).
- Ren, F., and Zhang, M. Bilateral single-issue negotiation model considering nonlinear utility and time constraint. Decision Support Systems. 60, 29-38. (2013).
- Rinaldi, S.M. Identifying, understanding and analyzing critical infrastructures interdependencies, IEEE Control Systems Magazine, 21(6), 11-25. (2001).
- Sandholm, T., and Likhodedov, A. Automated design of revenue-maximizing combinatorial auctions. Operations Research, 63(5), 1000-1025. (2015).
- Shao, S. Percolation of localized attack on complex networks, New Journal of Physics, 17, 023049. (2015).
- Smith, P. Network resilience: a systematic approach, IEEE Communications Magazine, 49(7), 88-97. (2011).
- Strogatz, S. H. Exploring complex networks. Nature, 410(6825), 268-276. (2001).
- Su, M.Y. A resilient routing approach for Mobile Ad Hoc Networks, International Conference on High Performance Computing & Simulation (HPCS). (2015).
- Wiener, H. Structural determination of paraffin boiling points. Journal of the American Chemical Society, 69(1):17-20, (1947).
- Xia, M., Stallaert, J. and A. B. Whinston. Solving the combinatorial double auction problem. European Journal of Operational Research 164(1), 239-251. (2005).
- Yagan, O. and Gligor, V. Analysis of complex contagions in random multiplex networks. Physical Review E, 86(3), 036103. (2012).
- Yao,Y. EDAL: An Energy-Efficient, Delay-Aware, and Lifetime-Balancing Data Collection Protocol for Heterogeneous Wireless Sensor Networks, in IEEE/ACM Transactions on Networking, 23(3), 810- 823. (2015).
- Younis, M. Topology management techniques for tolerating node failures in wireless sensor networks: A survey, Computer Networks, 58, 254-283. (2014).
- Zmijewski, Reckless Driving on the Internet, http://research.dyn.com/2009/02/the-flap-heard-around -the-world/ .(2009).
Paper Citation
in Harvard Style
de la Hoz E., Gimenez-Guzman J., Lopez-Civera G., Marsa-Maestre I. and Orden D. (2016). TOWER: Topology Optimization for netWork Enhanced Resilience . In - DCCI, (ICETE 2016) ISBN , pages 0-0. DOI: 10.5220/0006017101210128
in Bibtex Style
@conference{dcci16,
author={Enrique de la Hoz and Jose Manuel Gimenez-Guzman and German Lopez-Civera and Ivan Marsa-Maestre and David Orden},
title={TOWER: Topology Optimization for netWork Enhanced Resilience},
booktitle={ - DCCI, (ICETE 2016)},
year={2016},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006017101210128},
isbn={},
}
in EndNote Style
TY - CONF
JO - - DCCI, (ICETE 2016)
TI - TOWER: Topology Optimization for netWork Enhanced Resilience
SN -
AU - de la Hoz E.
AU - Gimenez-Guzman J.
AU - Lopez-Civera G.
AU - Marsa-Maestre I.
AU - Orden D.
PY - 2016
SP - 0
EP - 0
DO - 10.5220/0006017101210128