Abstract
In a world that is heavily relying on connected computers for the efficient execution of most daily tasks, Computer Security is absolutely critical. Therefore, in order to perform a complete analysis, new models and paradigms are needed to better manage the complexity of systems for an automated and data-driven economy. In past work we have described a bio-inspired approach that leverages metabolic networks to enhance and facilitate the use of attack-graph analysis to evaluate the security of systems, namely the BIAM framework. In this paper we describe the application of the BIAM framework to the search, analysis and assessment of the vulnerabilities of a simulated real-world use-case in the field of home-automation and ambient-intelligence.
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References
Alhomidi, M.A., Reed, M.J.: Attack graphs representations. In: 4th Computer Science and Electronic Engineering Conference (2012)
Vitabile, S., Conti, V., Lanza, B., Cusumano, D., Sorbello, F.: Metabolic Networks Robustness: theory, simulations and results. J. Interconnect. Netw. 12(3), 221–240 (2011)
Conti, V., Ruffo, S.S., Vitabile, S., Barolli, L.: BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture. Soft. Comput. 23(4), 1133–1150 (2019)
Conti, V., Ziggiotto, A., Migliardi, M., Vitabile, S.: Bio-inspired security analysis for IoT scenarios. Int. J. Embedded Syst. 13(2), 221–235 (2020)
Conti, V., Militello, C., Rundo, L., Vitabile, S.: A novel bio-inspired approach for high-performance management in service-oriented networks. IEEE Trans. Emerg. Top. Comput. 9(4), 1709–1722 (2021)
Vitello, G., Alongi, A., Conti, V., Vitabile, S.: A bio-inspired cognitive agent for autonomous urban vehicles routing optimization. IEEE Trans. Cogn. Dev. Syst. 9(1), 5–15 (2017)
Ko, H., Ramos, C.: A survey of context classfication for intelligent systems research for ambient intelligence. Int. Conf. Complex, Intell. Softw. Intensive Syst. (2010)
Phillips, C., Swiler, L.P.: A graph-based system for network vulnerability analysis. In: Proceedings of New Security Paradigms, pp. 71–79 (1998)
Chokshi, I., Das, S., Ghosh, N., Ghosh, S., Kaushik, A., Sarkar, M.: NetSecuritas: an integrated attack graph-based security assessment tool for enterprise network. In: Proceedings of the International Conference on Distributed Computing and Networking (2015)
Ammann, P., Pamula, J., Ritchey, R., Street, J.: A host-based approach to network attack chaining analysis. In: 21st Annual Computer Security Applications Conference, pp. 10–84 (2005)
Zhang, T., Ming-Zeng, H., Li, D., Sun, L.: An effective method to generate attack graph. Int. Conf. Mach. Learn. Cybern. 7, 3926–3931 (2005)
Xiao, X., Zhang, T., Wang, H., Zhang, G.: A component-centric access graph based approach to network attack analysis. In: International Seminar on Future Information Technology and Management Engineering, pp. 171–176 (2008)
Liu, Z., Li, S., He, J., Xie, D., Deng, Z.: Complex network security analysis based on attack graph model. In: Second International Conference on Instrumentation, Measurement, Computer, Communication and Control, pp. 183–186 (2012)
Chao, Z., Huiqiang, W., Fangfang, G., Mo, Z., Yushu, Z.: A heuristic method of attack graph analysis for network security hardening. In: International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, pp. 43-47 (2014)
Gallon, L., Bascou, J.: CVSS attack graphs. In: Seventh International Conference on Signal Image Technology and Internet-Based Systems, pp. 24–31 (2011ğ)
Malzahn, D., Birnbaum, Z., Wright-Hamor, C.: Automated vulnerability testing via executable attack graphs. In: International Conference on Cyber Security and Protection of Digital Services, pp. 1–10 (2020)
Musa, T., et al.: Analysis of complex networks for security issues using attack graph. In: International Conference on Computer Communication and Informatics, pp. 1–6 (2019)
Guimerá, R., Amaral, L.A.N.: Functional cartography of complex metabolic network. Nature 433, 895–900 (2005)
Schilling, C.H., Letscher, D., Palsson, B.: Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J. Theor. Biol. 248, 203–229 (2000)
Wiback, J.S., Palsson, B.O.: Extreme pathway analysis of human red blood cell metabolism. Biophys. J . 83, 808–818 (2003)
Barbehenn, M.: A note on the complexity of Dijkstra’s algorithm for graphs with weighted vertices. IEEE Trans. Comput. 47(2), 263 (1998)
Provost, A., Bastin, G.: Metabolic flux analysis: an approach for solving non-stationary undetermined systems. In: Troch, I., Breitenecker, F., Editors, 5th MATHMOD, pp. 5–10 (2006)
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Conti, V., Gallo, A., Migliardi, M., Vitabile, S. (2023). Bio-Inspired Security Analysis: A Domotic Use-Case. In: Bravo, J., Urzáiz, G. (eds) Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023). UCAmI 2023. Lecture Notes in Networks and Systems, vol 841. Springer, Cham. https://doi.org/10.1007/978-3-031-48590-9_18
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