Abstract
In last decades, thanks to the large diffusion of Information and communications technologies, the cooperation of distributed systems has been facilitated with the aim to provide new services. One of the common aspect of this kind of systems is the presence of a network able to ensure the connectivity among the elements of the network. The connectivity is a fundamental prerequisite also in the context of critical infrastructures (CIs), which are defined as a specific kind of infrastructures able to provide the essential services that underpin the society and serve as the backbone of our nation’s economy, security, and health (i.e. transportation systems, gas and water distribution systems, financial services, etc). Due to their relevance, the identification of vulnerabilities in this kind of systems is a mandatory task in order to design adequate and effective defense strategies. To this end, in this chapter some of the most common methods for networks vulnerabilities identification are illustrated and compared in order to stress common aspects and differences.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Notice that the decision variables collected in the vectors of the matrix X consists of the subset of decision variables that represents the nodes deletion.
References
Arulselvan A, Commander CW, Elefteriadou L, Pardalos PM (2009) Detecting critical nodes in sparse graphs. Comput Oper Res 36(7):2193–2200
Berezin Y, Bashan A, Danziger MM, Li D, Havlin S (2015) Localized attacks on spatially embedded networks with dependencies. Sci Rep 5:8934
Bonacich P (2007) Some unique properties of eigenvector centrality. Soc Netw 29(4):555–564
Brandes U (2001) A faster algorithm for betweenness centrality. J Math Soc 25(2):163–177 ISO 690
Censor Y (1977) Pareto optimality in multiobjective problems. Appl Math Optim 4:41–59
Dinh TN, Xuan Y, Thai MT, Park EK, Znati T (2010) On approximation of new optimization methods for assessing network vulnerability. In: INFOCOM, 2010 Proceedings IEEE, San Diego, pp 1–9. IEEE
Esposito JM, Dunbar TW (2006) Maintaining wireless connectivity constraints for swarms in the presence of obstacles. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA’06, Orlando, pp 946–951. IEEE
Faramondi L, Oliva G, Pascucci F, Panzieri S, Setola R (2016) Critical node detection based on attacker preferences. In: 2016 24th Mediterranean Conference on Control and Automation (MED), Athens, pp 773–778. IEEE
Faramondi L, Setola R, Panzieri S, Pascucci F, Oliva G (2017) Finding critical nodes in infrastructure networks. Int J Crit Infrastruct Prot 20:3–15
Faramondi L, Oliva G, Panzieri S, Pascucci F, Schlueter M, Munetomo M, Setola R (2018) Network structural vulnerability: a multiobjective attacker perspective. IEEE Trans Syst Man Cybern Syst
Holme P, Kim BJ, Yoon CN, Han SK (2002) Attack vulnerability of complex networks. Phys Rev E 65(5):056109
Huang X, Gao J, Buldyrev SV, Havlin S, Stanley HE (2011) Robustness of interdependent networks under targeted attack. Phys Rev E 83:065101
ICS-CERT USDHS (2014) ICS-monitor incident response activity. National Cybersecurity and Communications Integration Center
Lalou M, Tahraoui MA, Kheddouci H (2016) Component-cardinality-constrained critical node problem in graphs. Discret Appl Math 210:150–163
Lalou M, Tahraoui MA, Kheddouci H (2018) The critical node detection problem in networks: a survey. Comput Sci Rev 28:92–117
Louzada VHP, Daolio F, Herrmann HJ, Tomassini M (2015) Generating robust and efficient networks under targeted attacks. In: Dariusz K, Damien F, Bogdan G (eds) Propagation phenomena in real world networks. Springer, Cham/Heidelberg/New York/Dordrecht/London, pp 215–224
Lu ZM, Li XF (2016) Attack vulnerability of network controllability. PloS One 11(9):e0162289
Pullan W (2015) Heuristic identification of critical nodes in sparse real-world graphs. J Heuristics 21(5):577–598
Réka A, Hawoong J, Barabási A (2000) Error and attack tolerance of complex networks. Nature 406(6794):378–382
Schrijver A (1998) Theory of linear and integer programming. Wiley, Chichester/New York
Shao S, Huang X, Stanley HE, Havlin S (2015) Percolation of localized attack on complex networks. New J Phys 17(2):023049
Shen Y, Nguyen NP, Xuan Y, Thai MT (2013) On the discovery of critical links and nodes for assessing network vulnerability. IEEE/ACM Trans Netw (TON) 21(3):963–973
Sun F, Shayman MA (2007) On pairwise connectivity of wireless multihop networks. Int J Secur Netw 2(1–2):37–49
Ventresca M, Harrison KR, Ombuki-Berman BM (2015) An experimental evaluation of multi-objective evolutionary algorithms for detecting critical nodes in complex networks. In: European Conference on the Applications of Evolutionary Computation, Copenhagen, pp 164–176. Springer
Wu J, Deng HZ, Tan YJ, Zhu DZ (2007) Vulnerability of complex networks under intentional attack with incomplete information. J Phys A Math Theor 40(11):2665
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Faramondi, L., Setola, R. (2019). Identification of Vulnerabilities in Networked Systems. In: Gritzalis, D., Theocharidou, M., Stergiopoulos, G. (eds) Critical Infrastructure Security and Resilience. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-00024-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-00024-0_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00023-3
Online ISBN: 978-3-030-00024-0
eBook Packages: Computer ScienceComputer Science (R0)