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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1400))

Abstract

Context: Within digital ecosystems avoiding the propagation of security and trust violations among interconnected parties is a mandatory requirement, especially when a new device, a software component, or a system component is integrated within the ecosystem. Objective: The aim is to define an auditing framework able to assess and evaluate the specific functional and non-functional properties of the ecosystems and their components. Method: In this paper, we present the concept of predictive simulation and runtime monitoring for detecting malicious behavior of ecosystem components. Results and Conclusion: We defined a reference architecture allowing the automation of the auditing process for the runtime behavior verification of ecosystems and their components. Validation of the proposal with real use-cases is part of the future BIECO’s activities.

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Notes

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    https://activemq.apache.org/.

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Acknowledgement

This work was partially supported by the EU H2020 BIECO project GA No. 952702 (www.bieco.org).

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Correspondence to Said Daoudagh .

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Calabrò, A., Cioroaica, E., Daoudagh, S., Marchetti, E. (2022). BIECO Runtime Auditing Framework. In: Gude Prego, J.J., de la Puerta, J.G., García Bringas, P., Quintián, H., Corchado, E. (eds) 14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European Transnational Educational (CISIS 2021 and ICEUTE 2021). CISIS - ICEUTE 2021. Advances in Intelligent Systems and Computing, vol 1400. Springer, Cham. https://doi.org/10.1007/978-3-030-87872-6_18

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